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Duplicate from McAuley-Lab/Amazon-Reviews-2023

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Co-authored-by: Zhankui He <ZhankuiHe@users.noreply.huggingface.co>

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  1. .gitattributes +60 -0
  2. Amazon-Reviews-2023.py +557 -0
  3. README.md +733 -0
  4. all_categories.txt +34 -0
  5. asin2category.json +3 -0
  6. benchmark/0core/last_out/All_Beauty.test.csv +3 -0
  7. benchmark/0core/last_out/All_Beauty.train.csv +3 -0
  8. benchmark/0core/last_out/All_Beauty.valid.csv +3 -0
  9. benchmark/0core/last_out/Amazon_Fashion.test.csv +3 -0
  10. benchmark/0core/last_out/Amazon_Fashion.train.csv +3 -0
  11. benchmark/0core/last_out/Amazon_Fashion.valid.csv +3 -0
  12. benchmark/0core/last_out/Appliances.test.csv +3 -0
  13. benchmark/0core/last_out/Appliances.train.csv +3 -0
  14. benchmark/0core/last_out/Appliances.valid.csv +3 -0
  15. benchmark/0core/last_out/Arts_Crafts_and_Sewing.test.csv +3 -0
  16. benchmark/0core/last_out/Arts_Crafts_and_Sewing.train.csv +3 -0
  17. benchmark/0core/last_out/Arts_Crafts_and_Sewing.valid.csv +3 -0
  18. benchmark/0core/last_out/Automotive.test.csv +3 -0
  19. benchmark/0core/last_out/Automotive.train.csv +3 -0
  20. benchmark/0core/last_out/Automotive.valid.csv +3 -0
  21. benchmark/0core/last_out/Baby_Products.test.csv +3 -0
  22. benchmark/0core/last_out/Baby_Products.train.csv +3 -0
  23. benchmark/0core/last_out/Baby_Products.valid.csv +3 -0
  24. benchmark/0core/last_out/Beauty_and_Personal_Care.test.csv +3 -0
  25. benchmark/0core/last_out/Beauty_and_Personal_Care.train.csv +3 -0
  26. benchmark/0core/last_out/Beauty_and_Personal_Care.valid.csv +3 -0
  27. benchmark/0core/last_out/Books.test.csv +3 -0
  28. benchmark/0core/last_out/Books.train.csv +3 -0
  29. benchmark/0core/last_out/Books.valid.csv +3 -0
  30. benchmark/0core/last_out/CDs_and_Vinyl.test.csv +3 -0
  31. benchmark/0core/last_out/CDs_and_Vinyl.train.csv +3 -0
  32. benchmark/0core/last_out/CDs_and_Vinyl.valid.csv +3 -0
  33. benchmark/0core/last_out/Cell_Phones_and_Accessories.test.csv +3 -0
  34. benchmark/0core/last_out/Cell_Phones_and_Accessories.train.csv +3 -0
  35. benchmark/0core/last_out/Cell_Phones_and_Accessories.valid.csv +3 -0
  36. benchmark/0core/last_out/Clothing_Shoes_and_Jewelry.test.csv +3 -0
  37. benchmark/0core/last_out/Clothing_Shoes_and_Jewelry.train.csv +3 -0
  38. benchmark/0core/last_out/Clothing_Shoes_and_Jewelry.valid.csv +3 -0
  39. benchmark/0core/last_out/Digital_Music.test.csv +3 -0
  40. benchmark/0core/last_out/Digital_Music.train.csv +3 -0
  41. benchmark/0core/last_out/Digital_Music.valid.csv +3 -0
  42. benchmark/0core/last_out/Electronics.test.csv +3 -0
  43. benchmark/0core/last_out/Electronics.train.csv +3 -0
  44. benchmark/0core/last_out/Electronics.valid.csv +3 -0
  45. benchmark/0core/last_out/Gift_Cards.test.csv +3 -0
  46. benchmark/0core/last_out/Gift_Cards.train.csv +3 -0
  47. benchmark/0core/last_out/Gift_Cards.valid.csv +3 -0
  48. benchmark/0core/last_out/Grocery_and_Gourmet_Food.test.csv +3 -0
  49. benchmark/0core/last_out/Grocery_and_Gourmet_Food.train.csv +3 -0
  50. benchmark/0core/last_out/Grocery_and_Gourmet_Food.valid.csv +3 -0
.gitattributes ADDED
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.bz2 filter=lfs diff=lfs merge=lfs -text
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+ *.ckpt filter=lfs diff=lfs merge=lfs -text
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+ *.ftz filter=lfs diff=lfs merge=lfs -text
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+ *.gz filter=lfs diff=lfs merge=lfs -text
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+ *.h5 filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.lz4 filter=lfs diff=lfs merge=lfs -text
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+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ *.npy filter=lfs diff=lfs merge=lfs -text
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+ *.npz filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.ot filter=lfs diff=lfs merge=lfs -text
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+ *.parquet filter=lfs diff=lfs merge=lfs -text
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+ *.pb filter=lfs diff=lfs merge=lfs -text
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+ *.pickle filter=lfs diff=lfs merge=lfs -text
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+ *.pkl filter=lfs diff=lfs merge=lfs -text
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+ *.pt filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.tgz filter=lfs diff=lfs merge=lfs -text
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+ *.wasm filter=lfs diff=lfs merge=lfs -text
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+ *.xz filter=lfs diff=lfs merge=lfs -text
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+ *.zip filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ *.pcm filter=lfs diff=lfs merge=lfs -text
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+ *.sam filter=lfs diff=lfs merge=lfs -text
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+ *.raw filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - compressed
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+ *.aac filter=lfs diff=lfs merge=lfs -text
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+ *.flac filter=lfs diff=lfs merge=lfs -text
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+ *.mp3 filter=lfs diff=lfs merge=lfs -text
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+ *.ogg filter=lfs diff=lfs merge=lfs -text
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+ *.wav filter=lfs diff=lfs merge=lfs -text
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+ # Image files - uncompressed
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+ *.bmp filter=lfs diff=lfs merge=lfs -text
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+ *.gif filter=lfs diff=lfs merge=lfs -text
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+ *.png filter=lfs diff=lfs merge=lfs -text
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+ *.tiff filter=lfs diff=lfs merge=lfs -text
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+ # Image files - compressed
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+ *.jpg filter=lfs diff=lfs merge=lfs -text
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+ *.jpeg filter=lfs diff=lfs merge=lfs -text
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+ *.webp filter=lfs diff=lfs merge=lfs -text
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+ raw/review_categories/*.jsonl filter=lfs diff=lfs merge=lfs -text
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+ raw/meta_categories/*.jsonl filter=lfs diff=lfs merge=lfs -text
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+ group_by_user/*.jsonl filter=lfs diff=lfs merge=lfs -text
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+ benchmark/*/*/*.csv filter=lfs diff=lfs merge=lfs -text
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+ asin2category.json filter=lfs diff=lfs merge=lfs -text
Amazon-Reviews-2023.py ADDED
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+ import json
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+
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+ import datasets
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+
5
+
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+ _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-
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+ riptions, category information, price, brand, and images). Compared to the pre-
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+ vious versions, the 2023 version features larger size, newer reviews (up to Sep
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+ 2023), richer and cleaner meta data, and finer-grained timestamps (from day to
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+ 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 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - name: store
261
+ dtype: string
262
+ - name: categories
263
+ sequence: string
264
+ - name: details
265
+ dtype: string
266
+ - name: parent_asin
267
+ dtype: string
268
+ - name: bought_together
269
+ dtype: string
270
+ - name: subtitle
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
+ - name: title
285
+ dtype: string
286
+ - name: average_rating
287
+ dtype: float64
288
+ - name: rating_number
289
+ dtype: int64
290
+ - name: features
291
+ sequence: string
292
+ - name: description
293
+ sequence: string
294
+ - name: price
295
+ dtype: string
296
+ - name: images
297
+ sequence:
298
+ - name: hi_res
299
+ dtype: string
300
+ - name: large
301
+ dtype: string
302
+ - name: thumb
303
+ dtype: string
304
+ - name: variant
305
+ dtype: string
306
+ - name: videos
307
+ sequence:
308
+ - name: title
309
+ dtype: string
310
+ - name: url
311
+ dtype: string
312
+ - name: user_id
313
+ dtype: string
314
+ - name: store
315
+ dtype: string
316
+ - name: categories
317
+ sequence: string
318
+ - name: details
319
+ dtype: string
320
+ - name: parent_asin
321
+ dtype: string
322
+ - name: bought_together
323
+ dtype: string
324
+ - name: subtitle
325
+ dtype: string
326
+ - name: author
327
+ dtype: string
328
+ splits:
329
+ - 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
+ sequence: string
348
+ - name: price
349
+ dtype: string
350
+ - name: images
351
+ sequence:
352
+ - name: hi_res
353
+ dtype: string
354
+ - name: large
355
+ dtype: string
356
+ - name: thumb
357
+ dtype: string
358
+ - name: variant
359
+ dtype: string
360
+ - name: videos
361
+ sequence:
362
+ - name: title
363
+ dtype: string
364
+ - name: url
365
+ dtype: string
366
+ - name: user_id
367
+ dtype: string
368
+ - name: store
369
+ dtype: string
370
+ - name: categories
371
+ sequence: string
372
+ - name: details
373
+ dtype: string
374
+ - name: parent_asin
375
+ dtype: string
376
+ - name: bought_together
377
+ dtype: string
378
+ - name: subtitle
379
+ dtype: string
380
+ - name: author
381
+ dtype: string
382
+ splits:
383
+ - name: full
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
+ - name: title
393
+ dtype: string
394
+ - name: average_rating
395
+ dtype: float64
396
+ - name: rating_number
397
+ dtype: int64
398
+ - name: features
399
+ sequence: string
400
+ - name: description
401
+ sequence: string
402
+ - name: price
403
+ dtype: string
404
+ - name: images
405
+ sequence:
406
+ - name: hi_res
407
+ dtype: string
408
+ - name: large
409
+ dtype: string
410
+ - name: thumb
411
+ dtype: string
412
+ - name: variant
413
+ dtype: string
414
+ - name: videos
415
+ sequence:
416
+ - name: title
417
+ dtype: string
418
+ - name: url
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
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