Duplicate from McAuley-Lab/Amazon-Reviews-2023
Browse filesCo-authored-by: Zhankui He <ZhankuiHe@users.noreply.huggingface.co>
This view is limited to 50 files because it contains too many changes. See raw diff
- .gitattributes +60 -0
- Amazon-Reviews-2023.py +557 -0
- README.md +733 -0
- all_categories.txt +34 -0
- asin2category.json +3 -0
- benchmark/0core/last_out/All_Beauty.test.csv +3 -0
- benchmark/0core/last_out/All_Beauty.train.csv +3 -0
- benchmark/0core/last_out/All_Beauty.valid.csv +3 -0
- benchmark/0core/last_out/Amazon_Fashion.test.csv +3 -0
- benchmark/0core/last_out/Amazon_Fashion.train.csv +3 -0
- benchmark/0core/last_out/Amazon_Fashion.valid.csv +3 -0
- benchmark/0core/last_out/Appliances.test.csv +3 -0
- benchmark/0core/last_out/Appliances.train.csv +3 -0
- benchmark/0core/last_out/Appliances.valid.csv +3 -0
- benchmark/0core/last_out/Arts_Crafts_and_Sewing.test.csv +3 -0
- benchmark/0core/last_out/Arts_Crafts_and_Sewing.train.csv +3 -0
- benchmark/0core/last_out/Arts_Crafts_and_Sewing.valid.csv +3 -0
- benchmark/0core/last_out/Automotive.test.csv +3 -0
- benchmark/0core/last_out/Automotive.train.csv +3 -0
- benchmark/0core/last_out/Automotive.valid.csv +3 -0
- benchmark/0core/last_out/Baby_Products.test.csv +3 -0
- benchmark/0core/last_out/Baby_Products.train.csv +3 -0
- benchmark/0core/last_out/Baby_Products.valid.csv +3 -0
- benchmark/0core/last_out/Beauty_and_Personal_Care.test.csv +3 -0
- benchmark/0core/last_out/Beauty_and_Personal_Care.train.csv +3 -0
- benchmark/0core/last_out/Beauty_and_Personal_Care.valid.csv +3 -0
- benchmark/0core/last_out/Books.test.csv +3 -0
- benchmark/0core/last_out/Books.train.csv +3 -0
- benchmark/0core/last_out/Books.valid.csv +3 -0
- benchmark/0core/last_out/CDs_and_Vinyl.test.csv +3 -0
- benchmark/0core/last_out/CDs_and_Vinyl.train.csv +3 -0
- benchmark/0core/last_out/CDs_and_Vinyl.valid.csv +3 -0
- benchmark/0core/last_out/Cell_Phones_and_Accessories.test.csv +3 -0
- benchmark/0core/last_out/Cell_Phones_and_Accessories.train.csv +3 -0
- benchmark/0core/last_out/Cell_Phones_and_Accessories.valid.csv +3 -0
- benchmark/0core/last_out/Clothing_Shoes_and_Jewelry.test.csv +3 -0
- benchmark/0core/last_out/Clothing_Shoes_and_Jewelry.train.csv +3 -0
- benchmark/0core/last_out/Clothing_Shoes_and_Jewelry.valid.csv +3 -0
- benchmark/0core/last_out/Digital_Music.test.csv +3 -0
- benchmark/0core/last_out/Digital_Music.train.csv +3 -0
- benchmark/0core/last_out/Digital_Music.valid.csv +3 -0
- benchmark/0core/last_out/Electronics.test.csv +3 -0
- benchmark/0core/last_out/Electronics.train.csv +3 -0
- benchmark/0core/last_out/Electronics.valid.csv +3 -0
- benchmark/0core/last_out/Gift_Cards.test.csv +3 -0
- benchmark/0core/last_out/Gift_Cards.train.csv +3 -0
- benchmark/0core/last_out/Gift_Cards.valid.csv +3 -0
- benchmark/0core/last_out/Grocery_and_Gourmet_Food.test.csv +3 -0
- benchmark/0core/last_out/Grocery_and_Gourmet_Food.train.csv +3 -0
- benchmark/0core/last_out/Grocery_and_Gourmet_Food.valid.csv +3 -0
.gitattributes
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asin2category.json filter=lfs diff=lfs merge=lfs -text
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Amazon-Reviews-2023.py
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|
| 1 |
+
import json
|
| 2 |
+
|
| 3 |
+
import datasets
|
| 4 |
+
|
| 5 |
+
|
| 6 |
+
_AMAZON_REVIEW_2023_DESCRIPTION = """\
|
| 7 |
+
Amazon Review 2023 is an updated version of the Amazon Review 2018 dataset.
|
| 8 |
+
This dataset mainly includes reviews (ratings, text) and item metadata (desc-
|
| 9 |
+
riptions, category information, price, brand, and images). Compared to the pre-
|
| 10 |
+
vious versions, the 2023 version features larger size, newer reviews (up to Sep
|
| 11 |
+
2023), richer and cleaner meta data, and finer-grained timestamps (from day to
|
| 12 |
+
milli-second).
|
| 13 |
+
|
| 14 |
+
"""
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
class RawMetaAmazonReview2023Config(datasets.BuilderConfig):
|
| 18 |
+
def __init__(self, **kwargs):
|
| 19 |
+
super(RawMetaAmazonReview2023Config, self).__init__(**kwargs)
|
| 20 |
+
|
| 21 |
+
self.suffix = 'jsonl'
|
| 22 |
+
self.domain = self.name[len(f'raw_meta_'):]
|
| 23 |
+
self.description = f'This is a subset for items in domain: {self.domain}.'
|
| 24 |
+
self.data_dir = f'raw/meta_categories/meta_{self.domain}.jsonl'
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
class RawReviewAmazonReview2023Config(datasets.BuilderConfig):
|
| 28 |
+
def __init__(self, **kwargs):
|
| 29 |
+
super(RawReviewAmazonReview2023Config, self).__init__(**kwargs)
|
| 30 |
+
|
| 31 |
+
self.suffix = 'jsonl'
|
| 32 |
+
self.domain = self.name[len(f'raw_review_'):]
|
| 33 |
+
self.description = f'This is a subset for reviews in domain: {self.domain}.'
|
| 34 |
+
self.data_dir = f'raw/review_categories/{self.domain}.jsonl'
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
class RatingOnlyAmazonReview2023Config(datasets.BuilderConfig):
|
| 38 |
+
def __init__(self, **kwargs):
|
| 39 |
+
super(RatingOnlyAmazonReview2023Config, self).__init__(**kwargs)
|
| 40 |
+
|
| 41 |
+
self.suffix = 'csv'
|
| 42 |
+
self.kcore = self.name[:len('0core')]
|
| 43 |
+
self.domain = self.name[len(f'0core_rating_only_'):]
|
| 44 |
+
self.description = \
|
| 45 |
+
f'This is the preprocessed file that only contains <user, item, rating, timestamp> in domain: {self.domain}.\n' \
|
| 46 |
+
f'The preprocessing includes {self.kcore} filtering and <user, item> interaction deduplication'
|
| 47 |
+
self.data_dir = f'benchmark/{self.kcore}/rating_only/{self.domain}.csv'
|
| 48 |
+
|
| 49 |
+
|
| 50 |
+
class BenchmarkAmazonReview2023Config(datasets.BuilderConfig):
|
| 51 |
+
def __init__(self, **kwargs):
|
| 52 |
+
super(BenchmarkAmazonReview2023Config, self).__init__(**kwargs)
|
| 53 |
+
|
| 54 |
+
self.suffix = 'csv'
|
| 55 |
+
self.split = None
|
| 56 |
+
for potential_split in ['last_out_w_his', 'timestamp_w_his', 'last_out', 'timestamp']:
|
| 57 |
+
if potential_split in self.name:
|
| 58 |
+
self.split = potential_split
|
| 59 |
+
break
|
| 60 |
+
if self.split is None:
|
| 61 |
+
ValueError(f'Cannot find valid split for {self.name}')
|
| 62 |
+
self.kcore = self.name[:len('0core')]
|
| 63 |
+
self.domain = self.name[len(f'0core_{self.split}_'):]
|
| 64 |
+
self.description = \
|
| 65 |
+
f'This is the preprocessed benchmark in domain: {self.domain}.' \
|
| 66 |
+
f'The preprocessing includes {self.kcore} filtering, <user, item> interaction deduplication, ' \
|
| 67 |
+
f'as well as split by {self.split}.'
|
| 68 |
+
self.data_dir = {
|
| 69 |
+
'train': f'benchmark/{self.kcore}/{self.split}/{self.domain}.train.csv',
|
| 70 |
+
'valid': f'benchmark/{self.kcore}/{self.split}/{self.domain}.valid.csv',
|
| 71 |
+
'test': f'benchmark/{self.kcore}/{self.split}/{self.domain}.test.csv'
|
| 72 |
+
}
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
class AmazonReview2023(datasets.GeneratorBasedBuilder):
|
| 76 |
+
BUILDER_CONFIGS = [
|
| 77 |
+
# Raw item metadata
|
| 78 |
+
RawMetaAmazonReview2023Config(name='raw_meta_All_Beauty'),
|
| 79 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Toys_and_Games'),
|
| 80 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Cell_Phones_and_Accessories'),
|
| 81 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Industrial_and_Scientific'),
|
| 82 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Gift_Cards'),
|
| 83 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Musical_Instruments'),
|
| 84 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Electronics'),
|
| 85 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Handmade_Products'),
|
| 86 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Arts_Crafts_and_Sewing'),
|
| 87 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Baby_Products'),
|
| 88 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Health_and_Household'),
|
| 89 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Office_Products'),
|
| 90 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Digital_Music'),
|
| 91 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Grocery_and_Gourmet_Food'),
|
| 92 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Sports_and_Outdoors'),
|
| 93 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Home_and_Kitchen'),
|
| 94 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Subscription_Boxes'),
|
| 95 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Tools_and_Home_Improvement'),
|
| 96 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Pet_Supplies'),
|
| 97 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Video_Games'),
|
| 98 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Kindle_Store'),
|
| 99 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Clothing_Shoes_and_Jewelry'),
|
| 100 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Patio_Lawn_and_Garden'),
|
| 101 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Unknown'),
|
| 102 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Books'),
|
| 103 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Automotive'),
|
| 104 |
+
RawMetaAmazonReview2023Config(name='raw_meta_CDs_and_Vinyl'),
|
| 105 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Beauty_and_Personal_Care'),
|
| 106 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Amazon_Fashion'),
|
| 107 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Magazine_Subscriptions'),
|
| 108 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Software'),
|
| 109 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Health_and_Personal_Care'),
|
| 110 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Appliances'),
|
| 111 |
+
RawMetaAmazonReview2023Config(name='raw_meta_Movies_and_TV'),
|
| 112 |
+
# Raw review
|
| 113 |
+
RawReviewAmazonReview2023Config(name='raw_review_All_Beauty'),
|
| 114 |
+
RawReviewAmazonReview2023Config(name='raw_review_Toys_and_Games'),
|
| 115 |
+
RawReviewAmazonReview2023Config(name='raw_review_Cell_Phones_and_Accessories'),
|
| 116 |
+
RawReviewAmazonReview2023Config(name='raw_review_Industrial_and_Scientific'),
|
| 117 |
+
RawReviewAmazonReview2023Config(name='raw_review_Gift_Cards'),
|
| 118 |
+
RawReviewAmazonReview2023Config(name='raw_review_Musical_Instruments'),
|
| 119 |
+
RawReviewAmazonReview2023Config(name='raw_review_Electronics'),
|
| 120 |
+
RawReviewAmazonReview2023Config(name='raw_review_Handmade_Products'),
|
| 121 |
+
RawReviewAmazonReview2023Config(name='raw_review_Arts_Crafts_and_Sewing'),
|
| 122 |
+
RawReviewAmazonReview2023Config(name='raw_review_Baby_Products'),
|
| 123 |
+
RawReviewAmazonReview2023Config(name='raw_review_Health_and_Household'),
|
| 124 |
+
RawReviewAmazonReview2023Config(name='raw_review_Office_Products'),
|
| 125 |
+
RawReviewAmazonReview2023Config(name='raw_review_Digital_Music'),
|
| 126 |
+
RawReviewAmazonReview2023Config(name='raw_review_Grocery_and_Gourmet_Food'),
|
| 127 |
+
RawReviewAmazonReview2023Config(name='raw_review_Sports_and_Outdoors'),
|
| 128 |
+
RawReviewAmazonReview2023Config(name='raw_review_Home_and_Kitchen'),
|
| 129 |
+
RawReviewAmazonReview2023Config(name='raw_review_Subscription_Boxes'),
|
| 130 |
+
RawReviewAmazonReview2023Config(name='raw_review_Tools_and_Home_Improvement'),
|
| 131 |
+
RawReviewAmazonReview2023Config(name='raw_review_Pet_Supplies'),
|
| 132 |
+
RawReviewAmazonReview2023Config(name='raw_review_Video_Games'),
|
| 133 |
+
RawReviewAmazonReview2023Config(name='raw_review_Kindle_Store'),
|
| 134 |
+
RawReviewAmazonReview2023Config(name='raw_review_Clothing_Shoes_and_Jewelry'),
|
| 135 |
+
RawReviewAmazonReview2023Config(name='raw_review_Patio_Lawn_and_Garden'),
|
| 136 |
+
RawReviewAmazonReview2023Config(name='raw_review_Unknown'),
|
| 137 |
+
RawReviewAmazonReview2023Config(name='raw_review_Books'),
|
| 138 |
+
RawReviewAmazonReview2023Config(name='raw_review_Automotive'),
|
| 139 |
+
RawReviewAmazonReview2023Config(name='raw_review_CDs_and_Vinyl'),
|
| 140 |
+
RawReviewAmazonReview2023Config(name='raw_review_Beauty_and_Personal_Care'),
|
| 141 |
+
RawReviewAmazonReview2023Config(name='raw_review_Amazon_Fashion'),
|
| 142 |
+
RawReviewAmazonReview2023Config(name='raw_review_Magazine_Subscriptions'),
|
| 143 |
+
RawReviewAmazonReview2023Config(name='raw_review_Software'),
|
| 144 |
+
RawReviewAmazonReview2023Config(name='raw_review_Health_and_Personal_Care'),
|
| 145 |
+
RawReviewAmazonReview2023Config(name='raw_review_Appliances'),
|
| 146 |
+
RawReviewAmazonReview2023Config(name='raw_review_Movies_and_TV'),
|
| 147 |
+
# Rating only - 0core
|
| 148 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_All_Beauty'),
|
| 149 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Toys_and_Games'),
|
| 150 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Cell_Phones_and_Accessories'),
|
| 151 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Industrial_and_Scientific'),
|
| 152 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Gift_Cards'),
|
| 153 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Musical_Instruments'),
|
| 154 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Electronics'),
|
| 155 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Handmade_Products'),
|
| 156 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Arts_Crafts_and_Sewing'),
|
| 157 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Baby_Products'),
|
| 158 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Health_and_Household'),
|
| 159 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Office_Products'),
|
| 160 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Digital_Music'),
|
| 161 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Grocery_and_Gourmet_Food'),
|
| 162 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Sports_and_Outdoors'),
|
| 163 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Home_and_Kitchen'),
|
| 164 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Subscription_Boxes'),
|
| 165 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Tools_and_Home_Improvement'),
|
| 166 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Pet_Supplies'),
|
| 167 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Video_Games'),
|
| 168 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Kindle_Store'),
|
| 169 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Clothing_Shoes_and_Jewelry'),
|
| 170 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Patio_Lawn_and_Garden'),
|
| 171 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Unknown'),
|
| 172 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Books'),
|
| 173 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Automotive'),
|
| 174 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_CDs_and_Vinyl'),
|
| 175 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Beauty_and_Personal_Care'),
|
| 176 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Amazon_Fashion'),
|
| 177 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Magazine_Subscriptions'),
|
| 178 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Software'),
|
| 179 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Health_and_Personal_Care'),
|
| 180 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Appliances'),
|
| 181 |
+
RatingOnlyAmazonReview2023Config(name='0core_rating_only_Movies_and_TV'),
|
| 182 |
+
# Rating only - 5core
|
| 183 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_All_Beauty'),
|
| 184 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Toys_and_Games'),
|
| 185 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Cell_Phones_and_Accessories'),
|
| 186 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Industrial_and_Scientific'),
|
| 187 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Gift_Cards'),
|
| 188 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Musical_Instruments'),
|
| 189 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Electronics'),
|
| 190 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Arts_Crafts_and_Sewing'),
|
| 191 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Baby_Products'),
|
| 192 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Health_and_Household'),
|
| 193 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Office_Products'),
|
| 194 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Grocery_and_Gourmet_Food'),
|
| 195 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Sports_and_Outdoors'),
|
| 196 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Home_and_Kitchen'),
|
| 197 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Tools_and_Home_Improvement'),
|
| 198 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Pet_Supplies'),
|
| 199 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Video_Games'),
|
| 200 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Kindle_Store'),
|
| 201 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Clothing_Shoes_and_Jewelry'),
|
| 202 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Patio_Lawn_and_Garden'),
|
| 203 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Unknown'),
|
| 204 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Books'),
|
| 205 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Automotive'),
|
| 206 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_CDs_and_Vinyl'),
|
| 207 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Beauty_and_Personal_Care'),
|
| 208 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Magazine_Subscriptions'),
|
| 209 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Software'),
|
| 210 |
+
RatingOnlyAmazonReview2023Config(name='5core_rating_only_Movies_and_TV'),
|
| 211 |
+
# Benchmark - last_out - 0core
|
| 212 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_All_Beauty'),
|
| 213 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Toys_and_Games'),
|
| 214 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Cell_Phones_and_Accessories'),
|
| 215 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Industrial_and_Scientific'),
|
| 216 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Gift_Cards'),
|
| 217 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Musical_Instruments'),
|
| 218 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Electronics'),
|
| 219 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Handmade_Products'),
|
| 220 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Arts_Crafts_and_Sewing'),
|
| 221 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Baby_Products'),
|
| 222 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Health_and_Household'),
|
| 223 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Office_Products'),
|
| 224 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Digital_Music'),
|
| 225 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Grocery_and_Gourmet_Food'),
|
| 226 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Sports_and_Outdoors'),
|
| 227 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Home_and_Kitchen'),
|
| 228 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Subscription_Boxes'),
|
| 229 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Tools_and_Home_Improvement'),
|
| 230 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Pet_Supplies'),
|
| 231 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Video_Games'),
|
| 232 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Kindle_Store'),
|
| 233 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Clothing_Shoes_and_Jewelry'),
|
| 234 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Patio_Lawn_and_Garden'),
|
| 235 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Unknown'),
|
| 236 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Books'),
|
| 237 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Automotive'),
|
| 238 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_CDs_and_Vinyl'),
|
| 239 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Beauty_and_Personal_Care'),
|
| 240 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Amazon_Fashion'),
|
| 241 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Magazine_Subscriptions'),
|
| 242 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Software'),
|
| 243 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Health_and_Personal_Care'),
|
| 244 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Appliances'),
|
| 245 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_Movies_and_TV'),
|
| 246 |
+
# Benchmark - last_out - 5core
|
| 247 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_All_Beauty'),
|
| 248 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Toys_and_Games'),
|
| 249 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Cell_Phones_and_Accessories'),
|
| 250 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Industrial_and_Scientific'),
|
| 251 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Gift_Cards'),
|
| 252 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Musical_Instruments'),
|
| 253 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Electronics'),
|
| 254 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Arts_Crafts_and_Sewing'),
|
| 255 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Baby_Products'),
|
| 256 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Health_and_Household'),
|
| 257 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Office_Products'),
|
| 258 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Grocery_and_Gourmet_Food'),
|
| 259 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Sports_and_Outdoors'),
|
| 260 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Home_and_Kitchen'),
|
| 261 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Tools_and_Home_Improvement'),
|
| 262 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Pet_Supplies'),
|
| 263 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Video_Games'),
|
| 264 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Kindle_Store'),
|
| 265 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Clothing_Shoes_and_Jewelry'),
|
| 266 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Patio_Lawn_and_Garden'),
|
| 267 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Unknown'),
|
| 268 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Books'),
|
| 269 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Automotive'),
|
| 270 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_CDs_and_Vinyl'),
|
| 271 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Beauty_and_Personal_Care'),
|
| 272 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Magazine_Subscriptions'),
|
| 273 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Software'),
|
| 274 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_Movies_and_TV'),
|
| 275 |
+
# Benchmark - last_out_w_his - 0core
|
| 276 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_All_Beauty'),
|
| 277 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Toys_and_Games'),
|
| 278 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Cell_Phones_and_Accessories'),
|
| 279 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Industrial_and_Scientific'),
|
| 280 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Gift_Cards'),
|
| 281 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Musical_Instruments'),
|
| 282 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Electronics'),
|
| 283 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Handmade_Products'),
|
| 284 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Arts_Crafts_and_Sewing'),
|
| 285 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Baby_Products'),
|
| 286 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Health_and_Household'),
|
| 287 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Office_Products'),
|
| 288 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Digital_Music'),
|
| 289 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Grocery_and_Gourmet_Food'),
|
| 290 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Sports_and_Outdoors'),
|
| 291 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Home_and_Kitchen'),
|
| 292 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Subscription_Boxes'),
|
| 293 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Tools_and_Home_Improvement'),
|
| 294 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Pet_Supplies'),
|
| 295 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Video_Games'),
|
| 296 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Kindle_Store'),
|
| 297 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Clothing_Shoes_and_Jewelry'),
|
| 298 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Patio_Lawn_and_Garden'),
|
| 299 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Unknown'),
|
| 300 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Books'),
|
| 301 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Automotive'),
|
| 302 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_CDs_and_Vinyl'),
|
| 303 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Beauty_and_Personal_Care'),
|
| 304 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Amazon_Fashion'),
|
| 305 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Magazine_Subscriptions'),
|
| 306 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Software'),
|
| 307 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Health_and_Personal_Care'),
|
| 308 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Appliances'),
|
| 309 |
+
BenchmarkAmazonReview2023Config(name='0core_last_out_w_his_Movies_and_TV'),
|
| 310 |
+
# Benchmark - last_out_w_his - 5core
|
| 311 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_All_Beauty'),
|
| 312 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Toys_and_Games'),
|
| 313 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Cell_Phones_and_Accessories'),
|
| 314 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Industrial_and_Scientific'),
|
| 315 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Gift_Cards'),
|
| 316 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Musical_Instruments'),
|
| 317 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Electronics'),
|
| 318 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Arts_Crafts_and_Sewing'),
|
| 319 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Baby_Products'),
|
| 320 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Health_and_Household'),
|
| 321 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Office_Products'),
|
| 322 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Grocery_and_Gourmet_Food'),
|
| 323 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Sports_and_Outdoors'),
|
| 324 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Home_and_Kitchen'),
|
| 325 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Tools_and_Home_Improvement'),
|
| 326 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Pet_Supplies'),
|
| 327 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Video_Games'),
|
| 328 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Kindle_Store'),
|
| 329 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Clothing_Shoes_and_Jewelry'),
|
| 330 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Patio_Lawn_and_Garden'),
|
| 331 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Unknown'),
|
| 332 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Books'),
|
| 333 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Automotive'),
|
| 334 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_CDs_and_Vinyl'),
|
| 335 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Beauty_and_Personal_Care'),
|
| 336 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Magazine_Subscriptions'),
|
| 337 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Software'),
|
| 338 |
+
BenchmarkAmazonReview2023Config(name='5core_last_out_w_his_Movies_and_TV'),
|
| 339 |
+
# Benchmark - timestamp - 0core
|
| 340 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_All_Beauty'),
|
| 341 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Toys_and_Games'),
|
| 342 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Cell_Phones_and_Accessories'),
|
| 343 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Industrial_and_Scientific'),
|
| 344 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Gift_Cards'),
|
| 345 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Musical_Instruments'),
|
| 346 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Electronics'),
|
| 347 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Handmade_Products'),
|
| 348 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Arts_Crafts_and_Sewing'),
|
| 349 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Baby_Products'),
|
| 350 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Health_and_Household'),
|
| 351 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Office_Products'),
|
| 352 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Digital_Music'),
|
| 353 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Grocery_and_Gourmet_Food'),
|
| 354 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Sports_and_Outdoors'),
|
| 355 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Home_and_Kitchen'),
|
| 356 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Subscription_Boxes'),
|
| 357 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Tools_and_Home_Improvement'),
|
| 358 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Pet_Supplies'),
|
| 359 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Video_Games'),
|
| 360 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Kindle_Store'),
|
| 361 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Clothing_Shoes_and_Jewelry'),
|
| 362 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Patio_Lawn_and_Garden'),
|
| 363 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Unknown'),
|
| 364 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Books'),
|
| 365 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Automotive'),
|
| 366 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_CDs_and_Vinyl'),
|
| 367 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Beauty_and_Personal_Care'),
|
| 368 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Amazon_Fashion'),
|
| 369 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Magazine_Subscriptions'),
|
| 370 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Software'),
|
| 371 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Health_and_Personal_Care'),
|
| 372 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Appliances'),
|
| 373 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_Movies_and_TV'),
|
| 374 |
+
# Benchmark - timestamp - 5core
|
| 375 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_All_Beauty'),
|
| 376 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Toys_and_Games'),
|
| 377 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Cell_Phones_and_Accessories'),
|
| 378 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Industrial_and_Scientific'),
|
| 379 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Gift_Cards'),
|
| 380 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Musical_Instruments'),
|
| 381 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Electronics'),
|
| 382 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Arts_Crafts_and_Sewing'),
|
| 383 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Baby_Products'),
|
| 384 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Health_and_Household'),
|
| 385 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Office_Products'),
|
| 386 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Grocery_and_Gourmet_Food'),
|
| 387 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Sports_and_Outdoors'),
|
| 388 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Home_and_Kitchen'),
|
| 389 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Tools_and_Home_Improvement'),
|
| 390 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Pet_Supplies'),
|
| 391 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Video_Games'),
|
| 392 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Kindle_Store'),
|
| 393 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Clothing_Shoes_and_Jewelry'),
|
| 394 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Patio_Lawn_and_Garden'),
|
| 395 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Unknown'),
|
| 396 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Books'),
|
| 397 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Automotive'),
|
| 398 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_CDs_and_Vinyl'),
|
| 399 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Beauty_and_Personal_Care'),
|
| 400 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Magazine_Subscriptions'),
|
| 401 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Software'),
|
| 402 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_Movies_and_TV'),
|
| 403 |
+
# Benchmark - timestamp_w_his - 0core
|
| 404 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_All_Beauty'),
|
| 405 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Toys_and_Games'),
|
| 406 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Cell_Phones_and_Accessories'),
|
| 407 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Industrial_and_Scientific'),
|
| 408 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Gift_Cards'),
|
| 409 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Musical_Instruments'),
|
| 410 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Electronics'),
|
| 411 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Handmade_Products'),
|
| 412 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Arts_Crafts_and_Sewing'),
|
| 413 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Baby_Products'),
|
| 414 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Health_and_Household'),
|
| 415 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Office_Products'),
|
| 416 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Digital_Music'),
|
| 417 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Grocery_and_Gourmet_Food'),
|
| 418 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Sports_and_Outdoors'),
|
| 419 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Home_and_Kitchen'),
|
| 420 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Subscription_Boxes'),
|
| 421 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Tools_and_Home_Improvement'),
|
| 422 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Pet_Supplies'),
|
| 423 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Video_Games'),
|
| 424 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Kindle_Store'),
|
| 425 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Clothing_Shoes_and_Jewelry'),
|
| 426 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Patio_Lawn_and_Garden'),
|
| 427 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Unknown'),
|
| 428 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Books'),
|
| 429 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Automotive'),
|
| 430 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_CDs_and_Vinyl'),
|
| 431 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Beauty_and_Personal_Care'),
|
| 432 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Amazon_Fashion'),
|
| 433 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Magazine_Subscriptions'),
|
| 434 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Software'),
|
| 435 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Health_and_Personal_Care'),
|
| 436 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Appliances'),
|
| 437 |
+
BenchmarkAmazonReview2023Config(name='0core_timestamp_w_his_Movies_and_TV'),
|
| 438 |
+
# Benchmark - timestamp_w_his - 5core
|
| 439 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_All_Beauty'),
|
| 440 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Toys_and_Games'),
|
| 441 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Cell_Phones_and_Accessories'),
|
| 442 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Industrial_and_Scientific'),
|
| 443 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Gift_Cards'),
|
| 444 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Musical_Instruments'),
|
| 445 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Electronics'),
|
| 446 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Arts_Crafts_and_Sewing'),
|
| 447 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Baby_Products'),
|
| 448 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Health_and_Household'),
|
| 449 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Office_Products'),
|
| 450 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Grocery_and_Gourmet_Food'),
|
| 451 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Sports_and_Outdoors'),
|
| 452 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Home_and_Kitchen'),
|
| 453 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Tools_and_Home_Improvement'),
|
| 454 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Pet_Supplies'),
|
| 455 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Video_Games'),
|
| 456 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Kindle_Store'),
|
| 457 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Clothing_Shoes_and_Jewelry'),
|
| 458 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Patio_Lawn_and_Garden'),
|
| 459 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Unknown'),
|
| 460 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Books'),
|
| 461 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Automotive'),
|
| 462 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_CDs_and_Vinyl'),
|
| 463 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Beauty_and_Personal_Care'),
|
| 464 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Magazine_Subscriptions'),
|
| 465 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Software'),
|
| 466 |
+
BenchmarkAmazonReview2023Config(name='5core_timestamp_w_his_Movies_and_TV'),
|
| 467 |
+
]
|
| 468 |
+
|
| 469 |
+
def _info(self):
|
| 470 |
+
features = None
|
| 471 |
+
if isinstance(self.config, RawMetaAmazonReview2023Config):
|
| 472 |
+
features = datasets.Features({
|
| 473 |
+
'main_category': datasets.Value('string'),
|
| 474 |
+
'title': datasets.Value('string'),
|
| 475 |
+
'average_rating': datasets.Value(dtype='float64'),
|
| 476 |
+
'rating_number': datasets.Value(dtype='int64'),
|
| 477 |
+
'features': datasets.Sequence(datasets.Value('string')),
|
| 478 |
+
'description': datasets.Sequence(datasets.Value('string')),
|
| 479 |
+
'price': datasets.Value('string'),
|
| 480 |
+
'images': datasets.Sequence({
|
| 481 |
+
'hi_res': datasets.Value('string'),
|
| 482 |
+
'large': datasets.Value('string'),
|
| 483 |
+
'thumb': datasets.Value('string'),
|
| 484 |
+
'variant': datasets.Value('string')
|
| 485 |
+
}),
|
| 486 |
+
'videos': datasets.Sequence({
|
| 487 |
+
'title': datasets.Value('string'),
|
| 488 |
+
'url': datasets.Value('string'),
|
| 489 |
+
'user_id': datasets.Value('string')
|
| 490 |
+
}),
|
| 491 |
+
'store': datasets.Value('string'),
|
| 492 |
+
'categories': datasets.Sequence(datasets.Value('string')),
|
| 493 |
+
'details': datasets.Value('string'),
|
| 494 |
+
'parent_asin': datasets.Value('string'),
|
| 495 |
+
'bought_together': datasets.Value('string'), # TODO: Check this type
|
| 496 |
+
'subtitle': datasets.Value('string'),
|
| 497 |
+
'author': datasets.Value('string')
|
| 498 |
+
})
|
| 499 |
+
elif isinstance(self.config, RawReviewAmazonReview2023Config):
|
| 500 |
+
# TODO: Check review features
|
| 501 |
+
pass
|
| 502 |
+
|
| 503 |
+
return datasets.DatasetInfo(
|
| 504 |
+
description=_AMAZON_REVIEW_2023_DESCRIPTION + self.config.description,
|
| 505 |
+
features=features
|
| 506 |
+
)
|
| 507 |
+
|
| 508 |
+
def _split_generators(self, dl_manager):
|
| 509 |
+
dl_dir = dl_manager.download_and_extract(self.config.data_dir)
|
| 510 |
+
if isinstance(self.config, BenchmarkAmazonReview2023Config):
|
| 511 |
+
return [
|
| 512 |
+
datasets.SplitGenerator(name='train', gen_kwargs={"filepath": dl_dir['train']}),
|
| 513 |
+
datasets.SplitGenerator(name='valid', gen_kwargs={"filepath": dl_dir['valid']}),
|
| 514 |
+
datasets.SplitGenerator(name='test', gen_kwargs={"filepath": dl_dir['test']}),
|
| 515 |
+
]
|
| 516 |
+
else:
|
| 517 |
+
return [
|
| 518 |
+
datasets.SplitGenerator(name='full', gen_kwargs={"filepath": dl_dir})
|
| 519 |
+
]
|
| 520 |
+
|
| 521 |
+
def _generate_examples(self, filepath):
|
| 522 |
+
with open(filepath, 'r', encoding='utf-8') as file:
|
| 523 |
+
if self.config.suffix == 'csv':
|
| 524 |
+
colnames = file.readline().strip().split(',')
|
| 525 |
+
for idx, line in enumerate(file):
|
| 526 |
+
if self.config.suffix == 'jsonl':
|
| 527 |
+
try:
|
| 528 |
+
dp = json.loads(line)
|
| 529 |
+
"""
|
| 530 |
+
For item metadata, 'details' is free-form structured data
|
| 531 |
+
Here we dump it to string to make huggingface datasets easy
|
| 532 |
+
to store.
|
| 533 |
+
"""
|
| 534 |
+
if isinstance(self.config, RawMetaAmazonReview2023Config):
|
| 535 |
+
if 'details' in dp:
|
| 536 |
+
dp['details'] = json.dumps(dp['details'])
|
| 537 |
+
if 'price' in dp:
|
| 538 |
+
dp['price'] = str(dp['price'])
|
| 539 |
+
for optional_key in ['subtitle', 'author']:
|
| 540 |
+
if optional_key not in dp:
|
| 541 |
+
dp[optional_key] = None
|
| 542 |
+
for i in range(len(dp['images'])):
|
| 543 |
+
for k in ['hi_res', 'large', 'thumb', 'variant']:
|
| 544 |
+
if k not in dp['images'][i]:
|
| 545 |
+
dp['images'][i][k] = None
|
| 546 |
+
for i in range(len(dp['videos'])):
|
| 547 |
+
for k in ['title', 'url', 'user_id']:
|
| 548 |
+
if k not in dp['videos'][i]:
|
| 549 |
+
dp['videos'][i][k] = None
|
| 550 |
+
except:
|
| 551 |
+
continue
|
| 552 |
+
elif self.config.suffix == 'csv':
|
| 553 |
+
line = line.strip().split(',')
|
| 554 |
+
dp = {k: v for k, v in zip(colnames, line)}
|
| 555 |
+
else:
|
| 556 |
+
raise ValueError(f'Unknown suffix {self.config.suffix}.')
|
| 557 |
+
yield idx, dp
|
README.md
ADDED
|
@@ -0,0 +1,733 @@
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| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
tags:
|
| 5 |
+
- recommendation
|
| 6 |
+
- reviews
|
| 7 |
+
size_categories:
|
| 8 |
+
- 10B<n<100B
|
| 9 |
+
dataset_info:
|
| 10 |
+
- config_name: raw_meta_All_Beauty
|
| 11 |
+
features:
|
| 12 |
+
- name: main_category
|
| 13 |
+
dtype: string
|
| 14 |
+
- name: title
|
| 15 |
+
dtype: string
|
| 16 |
+
- name: average_rating
|
| 17 |
+
dtype: float64
|
| 18 |
+
- name: rating_number
|
| 19 |
+
dtype: int64
|
| 20 |
+
- name: features
|
| 21 |
+
sequence: string
|
| 22 |
+
- name: description
|
| 23 |
+
sequence: string
|
| 24 |
+
- name: price
|
| 25 |
+
dtype: string
|
| 26 |
+
- name: images
|
| 27 |
+
sequence:
|
| 28 |
+
- name: hi_res
|
| 29 |
+
dtype: string
|
| 30 |
+
- name: large
|
| 31 |
+
dtype: string
|
| 32 |
+
- name: thumb
|
| 33 |
+
dtype: string
|
| 34 |
+
- name: variant
|
| 35 |
+
dtype: string
|
| 36 |
+
- name: videos
|
| 37 |
+
sequence:
|
| 38 |
+
- name: title
|
| 39 |
+
dtype: string
|
| 40 |
+
- name: url
|
| 41 |
+
dtype: string
|
| 42 |
+
- name: user_id
|
| 43 |
+
dtype: string
|
| 44 |
+
- name: store
|
| 45 |
+
dtype: string
|
| 46 |
+
- name: categories
|
| 47 |
+
sequence: string
|
| 48 |
+
- name: details
|
| 49 |
+
dtype: string
|
| 50 |
+
- name: parent_asin
|
| 51 |
+
dtype: string
|
| 52 |
+
- name: bought_together
|
| 53 |
+
dtype: string
|
| 54 |
+
- name: subtitle
|
| 55 |
+
dtype: string
|
| 56 |
+
- name: author
|
| 57 |
+
dtype: string
|
| 58 |
+
splits:
|
| 59 |
+
- name: full
|
| 60 |
+
num_bytes: 172622243
|
| 61 |
+
num_examples: 112590
|
| 62 |
+
download_size: 59635138
|
| 63 |
+
dataset_size: 172622243
|
| 64 |
+
- config_name: raw_meta_Arts_Crafts_and_Sewing
|
| 65 |
+
features:
|
| 66 |
+
- name: main_category
|
| 67 |
+
dtype: string
|
| 68 |
+
- name: title
|
| 69 |
+
dtype: string
|
| 70 |
+
- name: average_rating
|
| 71 |
+
dtype: float64
|
| 72 |
+
- name: rating_number
|
| 73 |
+
dtype: int64
|
| 74 |
+
- name: features
|
| 75 |
+
sequence: string
|
| 76 |
+
- name: description
|
| 77 |
+
sequence: string
|
| 78 |
+
- name: price
|
| 79 |
+
dtype: string
|
| 80 |
+
- name: images
|
| 81 |
+
sequence:
|
| 82 |
+
- name: hi_res
|
| 83 |
+
dtype: string
|
| 84 |
+
- name: large
|
| 85 |
+
dtype: string
|
| 86 |
+
- name: thumb
|
| 87 |
+
dtype: string
|
| 88 |
+
- name: variant
|
| 89 |
+
dtype: string
|
| 90 |
+
- name: videos
|
| 91 |
+
sequence:
|
| 92 |
+
- name: title
|
| 93 |
+
dtype: string
|
| 94 |
+
- name: url
|
| 95 |
+
dtype: string
|
| 96 |
+
- name: user_id
|
| 97 |
+
dtype: string
|
| 98 |
+
- name: store
|
| 99 |
+
dtype: string
|
| 100 |
+
- name: categories
|
| 101 |
+
sequence: string
|
| 102 |
+
- name: details
|
| 103 |
+
dtype: string
|
| 104 |
+
- name: parent_asin
|
| 105 |
+
dtype: string
|
| 106 |
+
- name: bought_together
|
| 107 |
+
dtype: string
|
| 108 |
+
- name: subtitle
|
| 109 |
+
dtype: string
|
| 110 |
+
- name: author
|
| 111 |
+
dtype: string
|
| 112 |
+
splits:
|
| 113 |
+
- name: full
|
| 114 |
+
num_bytes: 1893257069
|
| 115 |
+
num_examples: 801446
|
| 116 |
+
download_size: 806711170
|
| 117 |
+
dataset_size: 1893257069
|
| 118 |
+
- config_name: raw_meta_Cell_Phones_and_Accessories
|
| 119 |
+
features:
|
| 120 |
+
- name: main_category
|
| 121 |
+
dtype: string
|
| 122 |
+
- name: title
|
| 123 |
+
dtype: string
|
| 124 |
+
- name: average_rating
|
| 125 |
+
dtype: float64
|
| 126 |
+
- name: rating_number
|
| 127 |
+
dtype: int64
|
| 128 |
+
- name: features
|
| 129 |
+
sequence: string
|
| 130 |
+
- name: description
|
| 131 |
+
sequence: string
|
| 132 |
+
- name: price
|
| 133 |
+
dtype: string
|
| 134 |
+
- name: images
|
| 135 |
+
sequence:
|
| 136 |
+
- name: hi_res
|
| 137 |
+
dtype: string
|
| 138 |
+
- name: large
|
| 139 |
+
dtype: string
|
| 140 |
+
- name: thumb
|
| 141 |
+
dtype: string
|
| 142 |
+
- name: variant
|
| 143 |
+
dtype: string
|
| 144 |
+
- name: videos
|
| 145 |
+
sequence:
|
| 146 |
+
- name: title
|
| 147 |
+
dtype: string
|
| 148 |
+
- name: url
|
| 149 |
+
dtype: string
|
| 150 |
+
- name: user_id
|
| 151 |
+
dtype: string
|
| 152 |
+
- name: store
|
| 153 |
+
dtype: string
|
| 154 |
+
- name: categories
|
| 155 |
+
sequence: string
|
| 156 |
+
- name: details
|
| 157 |
+
dtype: string
|
| 158 |
+
- name: parent_asin
|
| 159 |
+
dtype: string
|
| 160 |
+
- name: bought_together
|
| 161 |
+
dtype: string
|
| 162 |
+
- name: subtitle
|
| 163 |
+
dtype: string
|
| 164 |
+
- name: author
|
| 165 |
+
dtype: string
|
| 166 |
+
splits:
|
| 167 |
+
- name: full
|
| 168 |
+
num_bytes: 3497596478
|
| 169 |
+
num_examples: 1288490
|
| 170 |
+
download_size: 1262072469
|
| 171 |
+
dataset_size: 3497596478
|
| 172 |
+
- config_name: raw_meta_Electronics
|
| 173 |
+
features:
|
| 174 |
+
- name: main_category
|
| 175 |
+
dtype: string
|
| 176 |
+
- name: title
|
| 177 |
+
dtype: string
|
| 178 |
+
- name: average_rating
|
| 179 |
+
dtype: float64
|
| 180 |
+
- name: rating_number
|
| 181 |
+
dtype: int64
|
| 182 |
+
- name: features
|
| 183 |
+
sequence: string
|
| 184 |
+
- name: description
|
| 185 |
+
sequence: string
|
| 186 |
+
- name: price
|
| 187 |
+
dtype: string
|
| 188 |
+
- name: images
|
| 189 |
+
sequence:
|
| 190 |
+
- name: hi_res
|
| 191 |
+
dtype: string
|
| 192 |
+
- name: large
|
| 193 |
+
dtype: string
|
| 194 |
+
- name: thumb
|
| 195 |
+
dtype: string
|
| 196 |
+
- name: variant
|
| 197 |
+
dtype: string
|
| 198 |
+
- name: videos
|
| 199 |
+
sequence:
|
| 200 |
+
- name: title
|
| 201 |
+
dtype: string
|
| 202 |
+
- name: url
|
| 203 |
+
dtype: string
|
| 204 |
+
- name: user_id
|
| 205 |
+
dtype: string
|
| 206 |
+
- name: store
|
| 207 |
+
dtype: string
|
| 208 |
+
- name: categories
|
| 209 |
+
sequence: string
|
| 210 |
+
- name: details
|
| 211 |
+
dtype: string
|
| 212 |
+
- name: parent_asin
|
| 213 |
+
dtype: string
|
| 214 |
+
- name: bought_together
|
| 215 |
+
dtype: string
|
| 216 |
+
- name: subtitle
|
| 217 |
+
dtype: string
|
| 218 |
+
- name: author
|
| 219 |
+
dtype: string
|
| 220 |
+
splits:
|
| 221 |
+
- name: full
|
| 222 |
+
num_bytes: 4603602269
|
| 223 |
+
num_examples: 1610012
|
| 224 |
+
download_size: 1955009715
|
| 225 |
+
dataset_size: 4603602269
|
| 226 |
+
- config_name: raw_meta_Gift_Cards
|
| 227 |
+
features:
|
| 228 |
+
- name: main_category
|
| 229 |
+
dtype: string
|
| 230 |
+
- name: title
|
| 231 |
+
dtype: string
|
| 232 |
+
- name: average_rating
|
| 233 |
+
dtype: float64
|
| 234 |
+
- name: rating_number
|
| 235 |
+
dtype: int64
|
| 236 |
+
- name: features
|
| 237 |
+
sequence: string
|
| 238 |
+
- name: description
|
| 239 |
+
sequence: string
|
| 240 |
+
- name: price
|
| 241 |
+
dtype: string
|
| 242 |
+
- name: images
|
| 243 |
+
sequence:
|
| 244 |
+
- name: hi_res
|
| 245 |
+
dtype: string
|
| 246 |
+
- name: large
|
| 247 |
+
dtype: string
|
| 248 |
+
- name: thumb
|
| 249 |
+
dtype: string
|
| 250 |
+
- name: variant
|
| 251 |
+
dtype: string
|
| 252 |
+
- name: videos
|
| 253 |
+
sequence:
|
| 254 |
+
- name: title
|
| 255 |
+
dtype: string
|
| 256 |
+
- name: url
|
| 257 |
+
dtype: string
|
| 258 |
+
- name: user_id
|
| 259 |
+
dtype: string
|
| 260 |
+
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|
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+
dtype: string
|
| 262 |
+
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|
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sequence: string
|
| 264 |
+
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|
| 265 |
+
dtype: string
|
| 266 |
+
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|
| 267 |
+
dtype: string
|
| 268 |
+
- name: bought_together
|
| 269 |
+
dtype: string
|
| 270 |
+
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|
| 271 |
+
dtype: string
|
| 272 |
+
- name: author
|
| 273 |
+
dtype: string
|
| 274 |
+
splits:
|
| 275 |
+
- name: full
|
| 276 |
+
num_bytes: 1740761
|
| 277 |
+
num_examples: 1137
|
| 278 |
+
download_size: 401887
|
| 279 |
+
dataset_size: 1740761
|
| 280 |
+
- config_name: raw_meta_Handmade_Products
|
| 281 |
+
features:
|
| 282 |
+
- name: main_category
|
| 283 |
+
dtype: string
|
| 284 |
+
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|
| 285 |
+
dtype: string
|
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- name: average_rating
|
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+
dtype: float64
|
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+
- name: rating_number
|
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+
dtype: int64
|
| 290 |
+
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|
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+
sequence: string
|
| 292 |
+
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|
| 293 |
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sequence: string
|
| 294 |
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- name: price
|
| 295 |
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dtype: string
|
| 296 |
+
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|
| 297 |
+
sequence:
|
| 298 |
+
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|
| 299 |
+
dtype: string
|
| 300 |
+
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|
| 301 |
+
dtype: string
|
| 302 |
+
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|
| 303 |
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dtype: string
|
| 304 |
+
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|
| 305 |
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dtype: string
|
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- name: videos
|
| 307 |
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| 308 |
+
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|
| 309 |
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dtype: string
|
| 310 |
+
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|
| 311 |
+
dtype: string
|
| 312 |
+
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|
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|
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|
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|
| 317 |
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|
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|
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|
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|
| 321 |
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dtype: string
|
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|
| 323 |
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dtype: string
|
| 324 |
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|
| 325 |
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dtype: string
|
| 326 |
+
- name: author
|
| 327 |
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dtype: string
|
| 328 |
+
splits:
|
| 329 |
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- name: full
|
| 330 |
+
num_bytes: 340772183
|
| 331 |
+
num_examples: 164817
|
| 332 |
+
download_size: 132049123
|
| 333 |
+
dataset_size: 340772183
|
| 334 |
+
- config_name: raw_meta_Industrial_and_Scientific
|
| 335 |
+
features:
|
| 336 |
+
- name: main_category
|
| 337 |
+
dtype: string
|
| 338 |
+
- name: title
|
| 339 |
+
dtype: string
|
| 340 |
+
- name: average_rating
|
| 341 |
+
dtype: float64
|
| 342 |
+
- name: rating_number
|
| 343 |
+
dtype: int64
|
| 344 |
+
- name: features
|
| 345 |
+
sequence: string
|
| 346 |
+
- name: description
|
| 347 |
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sequence: string
|
| 348 |
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|
| 349 |
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dtype: string
|
| 350 |
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|
| 351 |
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|
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|
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|
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|
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| 359 |
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|
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|
| 362 |
+
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|
| 363 |
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dtype: string
|
| 364 |
+
- name: url
|
| 365 |
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dtype: string
|
| 366 |
+
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|
| 367 |
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|
| 368 |
+
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|
| 369 |
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|
| 371 |
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|
| 372 |
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|
| 373 |
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|
| 374 |
+
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|
| 375 |
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|
| 376 |
+
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|
| 377 |
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|
| 378 |
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|
| 379 |
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| 380 |
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|
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|
| 382 |
+
splits:
|
| 383 |
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|
| 384 |
+
num_bytes: 986632649
|
| 385 |
+
num_examples: 427564
|
| 386 |
+
download_size: 425007659
|
| 387 |
+
dataset_size: 986632649
|
| 388 |
+
- config_name: raw_meta_Musical_Instruments
|
| 389 |
+
features:
|
| 390 |
+
- name: main_category
|
| 391 |
+
dtype: string
|
| 392 |
+
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|
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|
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|
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|
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+
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|
| 419 |
+
dtype: string
|
| 420 |
+
- name: user_id
|
| 421 |
+
dtype: string
|
| 422 |
+
- name: store
|
| 423 |
+
dtype: string
|
| 424 |
+
- name: categories
|
| 425 |
+
sequence: string
|
| 426 |
+
- name: details
|
| 427 |
+
dtype: string
|
| 428 |
+
- name: parent_asin
|
| 429 |
+
dtype: string
|
| 430 |
+
- name: bought_together
|
| 431 |
+
dtype: string
|
| 432 |
+
- name: subtitle
|
| 433 |
+
dtype: string
|
| 434 |
+
- name: author
|
| 435 |
+
dtype: string
|
| 436 |
+
splits:
|
| 437 |
+
- name: full
|
| 438 |
+
num_bytes: 553296301
|
| 439 |
+
num_examples: 213593
|
| 440 |
+
download_size: 229633633
|
| 441 |
+
dataset_size: 553296301
|
| 442 |
+
- config_name: raw_meta_Toys_and_Games
|
| 443 |
+
features:
|
| 444 |
+
- name: main_category
|
| 445 |
+
dtype: string
|
| 446 |
+
- name: title
|
| 447 |
+
dtype: string
|
| 448 |
+
- name: average_rating
|
| 449 |
+
dtype: float64
|
| 450 |
+
- name: rating_number
|
| 451 |
+
dtype: int64
|
| 452 |
+
- name: features
|
| 453 |
+
sequence: string
|
| 454 |
+
- name: description
|
| 455 |
+
sequence: string
|
| 456 |
+
- name: price
|
| 457 |
+
dtype: string
|
| 458 |
+
- name: images
|
| 459 |
+
sequence:
|
| 460 |
+
- name: hi_res
|
| 461 |
+
dtype: string
|
| 462 |
+
- name: large
|
| 463 |
+
dtype: string
|
| 464 |
+
- name: thumb
|
| 465 |
+
dtype: string
|
| 466 |
+
- name: variant
|
| 467 |
+
dtype: string
|
| 468 |
+
- name: videos
|
| 469 |
+
sequence:
|
| 470 |
+
- name: title
|
| 471 |
+
dtype: string
|
| 472 |
+
- name: url
|
| 473 |
+
dtype: string
|
| 474 |
+
- name: user_id
|
| 475 |
+
dtype: string
|
| 476 |
+
- name: store
|
| 477 |
+
dtype: string
|
| 478 |
+
- name: categories
|
| 479 |
+
sequence: string
|
| 480 |
+
- name: details
|
| 481 |
+
dtype: string
|
| 482 |
+
- name: parent_asin
|
| 483 |
+
dtype: string
|
| 484 |
+
- name: bought_together
|
| 485 |
+
dtype: string
|
| 486 |
+
- name: subtitle
|
| 487 |
+
dtype: string
|
| 488 |
+
- name: author
|
| 489 |
+
dtype: string
|
| 490 |
+
splits:
|
| 491 |
+
- name: full
|
| 492 |
+
num_bytes: 2291736294
|
| 493 |
+
num_examples: 890874
|
| 494 |
+
download_size: 972667016
|
| 495 |
+
dataset_size: 2291736294
|
| 496 |
+
configs:
|
| 497 |
+
- config_name: raw_meta_All_Beauty
|
| 498 |
+
data_files:
|
| 499 |
+
- split: full
|
| 500 |
+
path: raw_meta_All_Beauty/full-*
|
| 501 |
+
- config_name: raw_meta_Arts_Crafts_and_Sewing
|
| 502 |
+
data_files:
|
| 503 |
+
- split: full
|
| 504 |
+
path: raw_meta_Arts_Crafts_and_Sewing/full-*
|
| 505 |
+
- config_name: raw_meta_Cell_Phones_and_Accessories
|
| 506 |
+
data_files:
|
| 507 |
+
- split: full
|
| 508 |
+
path: raw_meta_Cell_Phones_and_Accessories/full-*
|
| 509 |
+
- config_name: raw_meta_Electronics
|
| 510 |
+
data_files:
|
| 511 |
+
- split: full
|
| 512 |
+
path: raw_meta_Electronics/full-*
|
| 513 |
+
- config_name: raw_meta_Gift_Cards
|
| 514 |
+
data_files:
|
| 515 |
+
- split: full
|
| 516 |
+
path: raw_meta_Gift_Cards/full-*
|
| 517 |
+
- config_name: raw_meta_Handmade_Products
|
| 518 |
+
data_files:
|
| 519 |
+
- split: full
|
| 520 |
+
path: raw_meta_Handmade_Products/full-*
|
| 521 |
+
- config_name: raw_meta_Industrial_and_Scientific
|
| 522 |
+
data_files:
|
| 523 |
+
- split: full
|
| 524 |
+
path: raw_meta_Industrial_and_Scientific/full-*
|
| 525 |
+
- config_name: raw_meta_Musical_Instruments
|
| 526 |
+
data_files:
|
| 527 |
+
- split: full
|
| 528 |
+
path: raw_meta_Musical_Instruments/full-*
|
| 529 |
+
- config_name: raw_meta_Toys_and_Games
|
| 530 |
+
data_files:
|
| 531 |
+
- split: full
|
| 532 |
+
path: raw_meta_Toys_and_Games/full-*
|
| 533 |
+
---
|
| 534 |
+
|
| 535 |
+
# Amazon Reviews 2023
|
| 536 |
+
|
| 537 |
+
**Please also visit [amazon-reviews-2023.github.io/](https://amazon-reviews-2023.github.io/) for more details, loading scripts, and preprocessed benchmark files.**
|
| 538 |
+
|
| 539 |
+
**[April 7, 2024]** We add two useful files:
|
| 540 |
+
|
| 541 |
+
1. `all_categories.txt`: 34 lines (33 categories + "Unknown"), each line contains a category name.
|
| 542 |
+
2. `asin2category.json`: A mapping between `parent_asin` (item ID) to its corresponding category name.
|
| 543 |
+
|
| 544 |
+
---
|
| 545 |
+
|
| 546 |
+
<!-- Provide a quick summary of the dataset. -->
|
| 547 |
+
|
| 548 |
+
This is a large-scale **Amazon Reviews** dataset, collected in **2023** by [McAuley Lab](https://cseweb.ucsd.edu/~jmcauley/), and it includes rich features such as:
|
| 549 |
+
1. **User Reviews** (*ratings*, *text*, *helpfulness votes*, etc.);
|
| 550 |
+
2. **Item Metadata** (*descriptions*, *price*, *raw image*, etc.);
|
| 551 |
+
3. **Links** (*user-item* / *bought together* graphs).
|
| 552 |
+
|
| 553 |
+
## What's New?
|
| 554 |
+
|
| 555 |
+
In the Amazon Reviews'23, we provide:
|
| 556 |
+
|
| 557 |
+
1. **Larger Dataset:** We collected 571.54M reviews, 245.2% larger than the last version;
|
| 558 |
+
2. **Newer Interactions:** Current interactions range from May. 1996 to Sep. 2023;
|
| 559 |
+
3. **Richer Metadata:** More descriptive features in item metadata;
|
| 560 |
+
4. **Fine-grained Timestamp:** Interaction timestamp at the second or finer level;
|
| 561 |
+
5. **Cleaner Processing:** Cleaner item metadata than previous versions;
|
| 562 |
+
6. **Standard Splitting:** Standard data splits to encourage RecSys benchmarking.
|
| 563 |
+
|
| 564 |
+
## Basic Statistics
|
| 565 |
+
|
| 566 |
+
> We define the <b>#R_Tokens</b> as the number of [tokens](https://pypi.org/project/tiktoken/) in user reviews and <b>#M_Tokens</b> as the number of [tokens](https://pypi.org/project/tiktoken/) if treating the dictionaries of item attributes as strings. We emphasize them as important statistics in the era of LLMs.
|
| 567 |
+
|
| 568 |
+
> We count the number of items based on user reviews rather than item metadata files. Note that some items lack metadata.
|
| 569 |
+
|
| 570 |
+
### Compared to Previous Versions
|
| 571 |
+
|
| 572 |
+
| Year | #Review | #User | #Item | #R_Token | #M_Token | #Domain | Timespan |
|
| 573 |
+
| ----------- | ---------: | -------: | -------: | ---------: | ------------: | ------------: | ------------: |
|
| 574 |
+
| [2013](https://snap.stanford.edu/data/web-Amazon-links.html) | 34.69M | 6.64M | 2.44M | 5.91B | -- | 28 | Jun'96 - Mar'13 |
|
| 575 |
+
| [2014](https://cseweb.ucsd.edu/~jmcauley/datasets/amazon/links.html) | 82.83M | 21.13M | 9.86M | 9.16B | 4.14B | 24 | May'96 - Jul'14 |
|
| 576 |
+
| [2018](https://cseweb.ucsd.edu/~jmcauley/datasets/amazon_v2/) | 233.10M | 43.53M | 15.17M | 15.73B | 7.99B | 29 | May'96 - Oct'18 |
|
| 577 |
+
| <b>[2023](https://)</b> | **571.54M** | **54.51M** | **48.19M** | **30.14B** | **30.78B** | **33** | **May'96 - Sep'23** |
|
| 578 |
+
|
| 579 |
+
|
| 580 |
+
### Grouped by Category
|
| 581 |
+
|
| 582 |
+
| Category | #User | #Item | #Rating | #R_Token | #M_Token | Download |
|
| 583 |
+
| ------------------------ | ------: | ------: | --------: | -------: | -------: | ------------------------------: |
|
| 584 |
+
| All_Beauty | 632.0K | 112.6K | 701.5K | 31.6M | 74.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/All_Beauty.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_All_Beauty.jsonl.gz' download> meta </a> |
|
| 585 |
+
| Amazon_Fashion | 2.0M | 825.9K | 2.5M | 94.9M | 510.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Amazon_Fashion.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Amazon_Fashion.jsonl.gz' download> meta </a> |
|
| 586 |
+
| Appliances | 1.8M | 94.3K | 2.1M | 92.8M | 95.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Appliances.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Appliances.jsonl.gz' download> meta </a> |
|
| 587 |
+
| Arts_Crafts_and_Sewing | 4.6M | 801.3K | 9.0M | 350.0M | 695.4M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Arts_Crafts_and_Sewing.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Arts_Crafts_and_Sewing.jsonl.gz' download> meta </a> |
|
| 588 |
+
| Automotive | 8.0M | 2.0M | 20.0M | 824.9M | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Automotive.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Automotive.jsonl.gz' download> meta </a> |
|
| 589 |
+
| Baby_Products | 3.4M | 217.7K | 6.0M | 323.3M | 218.6M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Baby_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Baby_Products.jsonl.gz' download> meta </a> |
|
| 590 |
+
| Beauty_and_Personal_Care | 11.3M | 1.0M | 23.9M | 1.1B | 913.7M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Beauty_and_Personal_Care.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Beauty_and_Personal_Care.jsonl.gz' download> meta </a> |
|
| 591 |
+
| Books | 10.3M | 4.4M | 29.5M | 2.9B | 3.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Books.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Books.jsonl.gz' download> meta </a> |
|
| 592 |
+
| CDs_and_Vinyl | 1.8M | 701.7K | 4.8M | 514.8M | 287.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/CDs_and_Vinyl.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_CDs_and_Vinyl.jsonl.gz' download> meta </a> |
|
| 593 |
+
| Cell_Phones_and_Accessories | 11.6M | 1.3M | 20.8M | 935.4M | 1.3B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Cell_Phones_and_Accessories.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Cell_Phones_and_Accessories.jsonl.gz' download> meta </a> |
|
| 594 |
+
| Clothing_Shoes_and_Jewelry | 22.6M | 7.2M | 66.0M | 2.6B | 5.9B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Clothing_Shoes_and_Jewelry.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Clothing_Shoes_and_Jewelry.jsonl.gz' download> meta </a> |
|
| 595 |
+
| Digital_Music | 101.0K | 70.5K | 130.4K | 11.4M | 22.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Digital_Music.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Digital_Music.jsonl.gz' download> meta </a> |
|
| 596 |
+
| Electronics | 18.3M | 1.6M | 43.9M | 2.7B | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Electronics.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Electronics.jsonl.gz' download> meta </a> |
|
| 597 |
+
| Gift_Cards | 132.7K | 1.1K | 152.4K | 3.6M | 630.0K | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Gift_Cards.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Gift_Cards.jsonl.gz' download> meta </a> |
|
| 598 |
+
| Grocery_and_Gourmet_Food | 7.0M | 603.2K | 14.3M | 579.5M | 462.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Grocery_and_Gourmet_Food.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Grocery_and_Gourmet_Food.jsonl.gz' download> meta </a> |
|
| 599 |
+
| Handmade_Products | 586.6K | 164.7K | 664.2K | 23.3M | 125.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Handmade_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Handmade_Products.jsonl.gz' download> meta </a> |
|
| 600 |
+
| Health_and_Household | 12.5M | 797.4K | 25.6M | 1.2B | 787.2M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Health_and_Household.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Health_and_Household.jsonl.gz' download> meta </a> |
|
| 601 |
+
| Health_and_Personal_Care | 461.7K | 60.3K | 494.1K | 23.9M | 40.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Health_and_Personal_Care.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Health_and_Personal_Care.jsonl.gz' download> meta </a> |
|
| 602 |
+
| Home_and_Kitchen | 23.2M | 3.7M | 67.4M | 3.1B | 3.8B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Home_and_Kitchen.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Home_and_Kitchen.jsonl.gz' download> meta </a> |
|
| 603 |
+
| Industrial_and_Scientific | 3.4M | 427.5K | 5.2M | 235.2M | 363.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Industrial_and_Scientific.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Industrial_and_Scientific.jsonl.gz' download> meta </a> |
|
| 604 |
+
| Kindle_Store | 5.6M | 1.6M | 25.6M | 2.2B | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Kindle_Store.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Kindle_Store.jsonl.gz' download> meta </a> |
|
| 605 |
+
| Magazine_Subscriptions | 60.1K | 3.4K | 71.5K | 3.8M | 1.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Magazine_Subscriptions.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Magazine_Subscriptions.jsonl.gz' download> meta </a> |
|
| 606 |
+
| Movies_and_TV | 6.5M | 747.8K | 17.3M | 1.0B | 415.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Movies_and_TV.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Movies_and_TV.jsonl.gz' download> meta </a> |
|
| 607 |
+
| Musical_Instruments | 1.8M | 213.6K | 3.0M | 182.2M | 200.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Musical_Instruments.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Musical_Instruments.jsonl.gz' download> meta </a> |
|
| 608 |
+
| Office_Products | 7.6M | 710.4K | 12.8M | 574.7M | 682.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Office_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Office_Products.jsonl.gz' download> meta </a> |
|
| 609 |
+
| Patio_Lawn_and_Garden | 8.6M | 851.7K | 16.5M | 781.3M | 875.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Patio_Lawn_and_Garden.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Patio_Lawn_and_Garden.jsonl.gz' download> meta </a> |
|
| 610 |
+
| Pet_Supplies | 7.8M | 492.7K | 16.8M | 905.9M | 511.0M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Pet_Supplies.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Pet_Supplies.jsonl.gz' download> meta </a> |
|
| 611 |
+
| Software | 2.6M | 89.2K | 4.9M | 179.4M | 67.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Software.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Software.jsonl.gz' download> meta </a> |
|
| 612 |
+
| Sports_and_Outdoors | 10.3M | 1.6M | 19.6M | 986.2M | 1.3B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Sports_and_Outdoors.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Sports_and_Outdoors.jsonl.gz' download> meta </a> |
|
| 613 |
+
| Subscription_Boxes | 15.2K | 641 | 16.2K | 1.0M | 447.0K | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Subscription_Boxes.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Subscription_Boxes.jsonl.gz' download> meta </a> |
|
| 614 |
+
| Tools_and_Home_Improvement | 12.2M | 1.5M | 27.0M | 1.3B | 1.5B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Tools_and_Home_Improvement.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Tools_and_Home_Improvement.jsonl.gz' download> meta </a> |
|
| 615 |
+
| Toys_and_Games | 8.1M | 890.7K | 16.3M | 707.9M | 848.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Toys_and_Games.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Toys_and_Games.jsonl.gz' download> meta </a> |
|
| 616 |
+
| Video_Games | 2.8M | 137.2K | 4.6M | 347.9M | 137.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Video_Games.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Video_Games.jsonl.gz' download> meta </a> |
|
| 617 |
+
| Unknown | 23.1M | 13.2M | 63.8M | 3.3B | 232.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Unknown.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Unknown.jsonl.gz' download> meta </a> |
|
| 618 |
+
|
| 619 |
+
|
| 620 |
+
> Check Pure ID files and corresponding data splitting strategies in <b>[Common Data Processing](https://amazon-reviews-2023.github.io/data_processing/index.html)</b> section.
|
| 621 |
+
|
| 622 |
+
## Quick Start
|
| 623 |
+
|
| 624 |
+
### Load User Reviews
|
| 625 |
+
|
| 626 |
+
|
| 627 |
+
```python
|
| 628 |
+
from datasets import load_dataset
|
| 629 |
+
|
| 630 |
+
dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_review_All_Beauty", trust_remote_code=True)
|
| 631 |
+
print(dataset["full"][0])
|
| 632 |
+
```
|
| 633 |
+
|
| 634 |
+
```json
|
| 635 |
+
{'rating': 5.0,
|
| 636 |
+
'title': 'Such a lovely scent but not overpowering.',
|
| 637 |
+
'text': "This spray is really nice. It smells really good, goes on really fine, and does the trick. I will say it feels like you need a lot of it though to get the texture I want. I have a lot of hair, medium thickness. I am comparing to other brands with yucky chemicals so I'm gonna stick with this. Try it!",
|
| 638 |
+
'images': [],
|
| 639 |
+
'asin': 'B00YQ6X8EO',
|
| 640 |
+
'parent_asin': 'B00YQ6X8EO',
|
| 641 |
+
'user_id': 'AGKHLEW2SOWHNMFQIJGBECAF7INQ',
|
| 642 |
+
'timestamp': 1588687728923,
|
| 643 |
+
'helpful_vote': 0,
|
| 644 |
+
'verified_purchase': True}
|
| 645 |
+
```
|
| 646 |
+
|
| 647 |
+
### Load Item Metadata
|
| 648 |
+
|
| 649 |
+
```python
|
| 650 |
+
dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_meta_All_Beauty", split="full", trust_remote_code=True)
|
| 651 |
+
print(dataset[0])
|
| 652 |
+
```
|
| 653 |
+
|
| 654 |
+
```json
|
| 655 |
+
{'main_category': 'All Beauty',
|
| 656 |
+
'title': 'Howard LC0008 Leather Conditioner, 8-Ounce (4-Pack)',
|
| 657 |
+
'average_rating': 4.8,
|
| 658 |
+
'rating_number': 10,
|
| 659 |
+
'features': [],
|
| 660 |
+
'description': [],
|
| 661 |
+
'price': 'None',
|
| 662 |
+
'images': {'hi_res': [None,
|
| 663 |
+
'https://m.media-amazon.com/images/I/71i77AuI9xL._SL1500_.jpg'],
|
| 664 |
+
'large': ['https://m.media-amazon.com/images/I/41qfjSfqNyL.jpg',
|
| 665 |
+
'https://m.media-amazon.com/images/I/41w2yznfuZL.jpg'],
|
| 666 |
+
'thumb': ['https://m.media-amazon.com/images/I/41qfjSfqNyL._SS40_.jpg',
|
| 667 |
+
'https://m.media-amazon.com/images/I/41w2yznfuZL._SS40_.jpg'],
|
| 668 |
+
'variant': ['MAIN', 'PT01']},
|
| 669 |
+
'videos': {'title': [], 'url': [], 'user_id': []},
|
| 670 |
+
'store': 'Howard Products',
|
| 671 |
+
'categories': [],
|
| 672 |
+
'details': '{"Package Dimensions": "7.1 x 5.5 x 3 inches; 2.38 Pounds", "UPC": "617390882781"}',
|
| 673 |
+
'parent_asin': 'B01CUPMQZE',
|
| 674 |
+
'bought_together': None,
|
| 675 |
+
'subtitle': None,
|
| 676 |
+
'author': None}
|
| 677 |
+
```
|
| 678 |
+
|
| 679 |
+
> Check data loading examples and Huggingface datasets APIs in <b>[Common Data Loading](https://amazon-reviews-2023.github.io/data_loading/index.html)</b> section.
|
| 680 |
+
|
| 681 |
+
|
| 682 |
+
## Data Fields
|
| 683 |
+
|
| 684 |
+
### For User Reviews
|
| 685 |
+
|
| 686 |
+
| Field | Type | Explanation |
|
| 687 |
+
| ----- | ---- | ----------- |
|
| 688 |
+
| rating | float | Rating of the product (from 1.0 to 5.0). |
|
| 689 |
+
| title | str | Title of the user review. |
|
| 690 |
+
| text | str | Text body of the user review. |
|
| 691 |
+
| images | list | Images that users post after they have received the product. Each image has different sizes (small, medium, large), represented by the small_image_url, medium_image_url, and large_image_url respectively. |
|
| 692 |
+
| asin | str | ID of the product. |
|
| 693 |
+
| parent_asin | str | Parent ID of the product. Note: Products with different colors, styles, sizes usually belong to the same parent ID. The “asin” in previous Amazon datasets is actually parent ID. <b>Please use parent ID to find product meta.</b> |
|
| 694 |
+
| user_id | str | ID of the reviewer |
|
| 695 |
+
| timestamp | int | Time of the review (unix time) |
|
| 696 |
+
| verified_purchase | bool | User purchase verification |
|
| 697 |
+
| helpful_vote | int | Helpful votes of the review |
|
| 698 |
+
|
| 699 |
+
### For Item Metadata
|
| 700 |
+
|
| 701 |
+
| Field | Type | Explanation |
|
| 702 |
+
| ----- | ---- | ----------- |
|
| 703 |
+
| main_category | str | Main category (i.e., domain) of the product. |
|
| 704 |
+
| title | str | Name of the product. |
|
| 705 |
+
| average_rating | float | Rating of the product shown on the product page. |
|
| 706 |
+
| rating_number | int | Number of ratings in the product. |
|
| 707 |
+
| features | list | Bullet-point format features of the product. |
|
| 708 |
+
| description | list | Description of the product. |
|
| 709 |
+
| price | float | Price in US dollars (at time of crawling). |
|
| 710 |
+
| images | list | Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image. |
|
| 711 |
+
| videos | list | Videos of the product including title and url. |
|
| 712 |
+
| store | str | Store name of the product. |
|
| 713 |
+
| categories | list | Hierarchical categories of the product. |
|
| 714 |
+
| details | dict | Product details, including materials, brand, sizes, etc. |
|
| 715 |
+
| parent_asin | str | Parent ID of the product. |
|
| 716 |
+
| bought_together | list | Recommended bundles from the websites. |
|
| 717 |
+
|
| 718 |
+
## Citation
|
| 719 |
+
|
| 720 |
+
```bibtex
|
| 721 |
+
@article{hou2024bridging,
|
| 722 |
+
title={Bridging Language and Items for Retrieval and Recommendation},
|
| 723 |
+
author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian},
|
| 724 |
+
journal={arXiv preprint arXiv:2403.03952},
|
| 725 |
+
year={2024}
|
| 726 |
+
}
|
| 727 |
+
```
|
| 728 |
+
|
| 729 |
+
## Contact Us
|
| 730 |
+
|
| 731 |
+
- **Report Bugs**: To report bugs in the dataset, please file an issue on our [GitHub](https://github.com/hyp1231/AmazonReviews2023/issues/new).
|
| 732 |
+
|
| 733 |
+
- **Others**: For research collaborations or other questions, please email **yphou AT ucsd.edu**.
|
all_categories.txt
ADDED
|
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
All_Beauty
|
| 2 |
+
Toys_and_Games
|
| 3 |
+
Cell_Phones_and_Accessories
|
| 4 |
+
Industrial_and_Scientific
|
| 5 |
+
Gift_Cards
|
| 6 |
+
Musical_Instruments
|
| 7 |
+
Electronics
|
| 8 |
+
Handmade_Products
|
| 9 |
+
Arts_Crafts_and_Sewing
|
| 10 |
+
Baby_Products
|
| 11 |
+
Health_and_Household
|
| 12 |
+
Office_Products
|
| 13 |
+
Digital_Music
|
| 14 |
+
Grocery_and_Gourmet_Food
|
| 15 |
+
Sports_and_Outdoors
|
| 16 |
+
Home_and_Kitchen
|
| 17 |
+
Subscription_Boxes
|
| 18 |
+
Tools_and_Home_Improvement
|
| 19 |
+
Pet_Supplies
|
| 20 |
+
Video_Games
|
| 21 |
+
Kindle_Store
|
| 22 |
+
Clothing_Shoes_and_Jewelry
|
| 23 |
+
Patio_Lawn_and_Garden
|
| 24 |
+
Unknown
|
| 25 |
+
Books
|
| 26 |
+
Automotive
|
| 27 |
+
CDs_and_Vinyl
|
| 28 |
+
Beauty_and_Personal_Care
|
| 29 |
+
Amazon_Fashion
|
| 30 |
+
Magazine_Subscriptions
|
| 31 |
+
Software
|
| 32 |
+
Health_and_Personal_Care
|
| 33 |
+
Appliances
|
| 34 |
+
Movies_and_TV
|
asin2category.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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+
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|
| 3 |
+
size 1246846569
|
benchmark/0core/last_out/All_Beauty.test.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 3 |
+
size 36655321
|
benchmark/0core/last_out/All_Beauty.train.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 1110519
|
benchmark/0core/last_out/All_Beauty.valid.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 2483851
|
benchmark/0core/last_out/Amazon_Fashion.test.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 118058587
|
benchmark/0core/last_out/Amazon_Fashion.train.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 9136701
|
benchmark/0core/last_out/Amazon_Fashion.valid.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 16321065
|
benchmark/0core/last_out/Appliances.test.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 101832586
|
benchmark/0core/last_out/Appliances.train.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 3 |
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size 6079589
|
benchmark/0core/last_out/Appliances.valid.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
benchmark/0core/last_out/Arts_Crafts_and_Sewing.test.csv
ADDED
|
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|
|
|
|
|
|
|
|
|
|
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version https://git-lfs.github.com/spec/v1
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size 268238377
|
benchmark/0core/last_out/Arts_Crafts_and_Sewing.train.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
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version https://git-lfs.github.com/spec/v1
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|
benchmark/0core/last_out/Arts_Crafts_and_Sewing.valid.csv
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
+
size 84012810
|
benchmark/0core/last_out/Automotive.test.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 465145425
|
benchmark/0core/last_out/Automotive.train.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
| 3 |
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size 487562849
|
benchmark/0core/last_out/Automotive.valid.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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size 189480357
|
benchmark/0core/last_out/Baby_Products.test.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 196400035
|
benchmark/0core/last_out/Baby_Products.train.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
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+
size 90027871
|
benchmark/0core/last_out/Baby_Products.valid.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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