FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction
Paper
•
2304.00902
•
Published
Search is not available for this dataset
label
int64 0
1
| user
int64 0
956
| item
int64 957
5.04k
| daytime
int64 5.04k
5.05k
| weekday
int64 5.05k
5.05k
| isweekend
int64 5.05k
5.05k
| homework
int64 5.06k
5.06k
| cost
int64 5.06k
5.06k
| weather
int64 5.06k
5.07k
| country
int64 5.07k
5.15k
| city
int64 5.15k
5.38k
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|---|---|---|---|---|---|---|---|---|---|---|
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0
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1
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0
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0
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1
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1
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0
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0
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0
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1
| 7
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0
| 50
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1
| 273
| 974
| 5,041
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0
| 127
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0
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0
| 80
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0
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1
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| 978
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1
| 180
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1
| 254
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0
| 47
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0
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1
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1
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0
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1
| 130
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0
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1
| 347
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0
| 77
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0
| 155
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0
| 179
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1
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0
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1
| 33
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0
| 59
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1
| 264
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0
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0
| 80
| 4,191
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| 5,048
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0
| 164
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0
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0
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0
| 377
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1
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1
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| 973
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0
| 86
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| 5,159
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1
| 1
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| 5,039
| 5,048
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| 5,070
| 5,150
|
0
| 46
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| 5,042
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|
1
| 85
| 1,919
| 5,040
| 5,051
| 5,054
| 5,055
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| 5,061
| 5,075
| 5,159
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1
| 236
| 974
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| 5,075
| 5,290
|
1
| 41
| 982
| 5,044
| 5,051
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| 5,085
| 5,149
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0
| 194
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|
0
| 87
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0
| 47
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| 5,155
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0
| 283
| 3,339
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0
| 160
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| 5,058
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| 5,070
| 5,150
|
0
| 48
| 3,064
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| 5,150
|
1
| 9
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| 5,062
| 5,074
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0
| 377
| 4,449
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0
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0
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0
| 24
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0
| 510
| 3,492
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|
1
| 232
| 978
| 5,040
| 5,050
| 5,054
| 5,055
| 5,058
| 5,061
| 5,069
| 5,185
|
1
| 9
| 983
| 5,044
| 5,047
| 5,053
| 5,055
| 5,058
| 5,062
| 5,074
| 5,149
|
0
| 91
| 3,319
| 5,040
| 5,047
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| 5,058
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| 5,095
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0
| 159
| 1,778
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| 5,155
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1
| 187
| 4,053
| 5,039
| 5,048
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| 5,055
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| 5,063
| 5,077
| 5,155
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0
| 220
| 3,413
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1
| 56
| 1,006
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| 5,052
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|
1
| 64
| 1,035
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| 5,070
| 5,150
|
0
| 37
| 3,247
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| 5,053
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| 5,058
| 5,064
| 5,073
| 5,161
|
0
| 117
| 4,691
| 5,041
| 5,046
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| 5,061
| 5,100
| 5,192
|
0
| 276
| 3,699
| 5,040
| 5,048
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| 5,055
| 5,058
| 5,061
| 5,070
| 5,149
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1
| 142
| 1,268
| 5,040
| 5,051
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| 5,056
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| 5,102
| 5,149
|
1
| 91
| 973
| 5,043
| 5,051
| 5,054
| 5,056
| 5,058
| 5,065
| 5,095
| 5,149
|
1
| 52
| 1,143
| 5,043
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| 5,061
| 5,075
| 5,167
|
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Frappe_x1
Dataset description:
The Frappe dataset contains a context-aware app usage log, which comprises 96203 entries by 957 users for 4082 apps used in various contexts. It has 10 feature fields including user_id, item_id, daytime, weekday, isweekend, homework, cost, weather, country, city. The target value indicates whether the user has used the app under the context. Following the AFN work, we randomly split the data into 7:2:1 as the training set, validation set, and test set, respectively.
The dataset statistics are summarized as follows:
Dataset Split Total #Train #Validation #Test Frappe_x1 288,609 202,027 57,722 28,860 Download: https://huggingface.co/datasets/reczoo/Frappe_x1/tree/main
Repository: https://github.com/reczoo/Datasets
Used by papers:
- Weiyu Cheng, Yanyan Shen, Linpeng Huang. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In AAAI 2020.
- Kelong Mao, Jieming Zhu, Liangcai Su, Guohao Cai, Yuru Li, Zhenhua Dong. FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction. In AAAI 2023.
- Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang. FINAL: Factorized Interaction Layer for CTR Prediction. In SIGIR 2023.
Check the md5sum for data integrity:
$ md5sum train.csv valid.csv test.csv ba7306e6c4fc19dd2cd84f2f0596d158 train.csv 88d51bf2173505436d3a8f78f2a59da8 valid.csv 3470f6d32713dc5f7715f198ca7c612a test.csv
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Size of downloaded dataset files:
2.8 MB
Size of the auto-converted Parquet files:
4.19 MB
Number of rows:
288,609