Search is not available for this dataset
label
int64 0
1
| user_id
int64 0
90.4k
| item_id
int64 1
90.4k
| tag_id
int64 2
69.1k
|
|---|---|---|---|
0
| 51,798
| 2,473
| 37,583
|
0
| 66,335
| 61,344
| 29,842
|
0
| 89,085
| 60,033
| 47,050
|
1
| 61,293
| 8,073
| 3,903
|
0
| 81,335
| 56,575
| 50,067
|
0
| 65,166
| 48,181
| 12,510
|
0
| 75,300
| 26,027
| 38,510
|
1
| 10,219
| 2,122
| 383
|
1
| 80,855
| 80,856
| 24,728
|
1
| 67,033
| 721
| 19,495
|
0
| 80,574
| 4,352
| 1,885
|
0
| 90,194
| 13,389
| 13,229
|
0
| 81,469
| 34,789
| 24,788
|
1
| 76,049
| 56,307
| 51,431
|
0
| 63,553
| 1,662
| 46,915
|
0
| 86,940
| 13,820
| 44,681
|
1
| 39,479
| 39,496
| 972
|
0
| 68,854
| 57,527
| 41,338
|
0
| 85,648
| 488
| 24,424
|
1
| 86,148
| 10,155
| 82
|
0
| 65,166
| 25,552
| 27,746
|
1
| 68,854
| 63,464
| 9,130
|
0
| 67,886
| 800
| 46,637
|
0
| 74,824
| 17,296
| 8,180
|
0
| 86,498
| 41,080
| 28,484
|
0
| 65,166
| 60,615
| 28,617
|
1
| 71,708
| 25,715
| 764
|
0
| 85,231
| 16,221
| 16,180
|
0
| 80,954
| 62,140
| 43,799
|
0
| 80,874
| 1,656
| 34,769
|
0
| 84,982
| 603
| 26,084
|
0
| 80,034
| 11,717
| 54,781
|
1
| 58,995
| 13,820
| 12,684
|
0
| 66,217
| 57,129
| 24,385
|
1
| 82,033
| 6,833
| 10,044
|
1
| 80,179
| 12,914
| 17,734
|
0
| 68,658
| 8,171
| 28,680
|
1
| 81,557
| 26,261
| 10,504
|
0
| 88,928
| 67,064
| 27,341
|
0
| 71,683
| 29,781
| 6,713
|
1
| 66,893
| 501
| 14,782
|
0
| 85,606
| 721
| 24,507
|
0
| 78,897
| 40,815
| 30,825
|
0
| 87,624
| 8,171
| 35,649
|
0
| 67,270
| 15,255
| 39,558
|
0
| 59,125
| 603
| 22,563
|
0
| 86,301
| 21,868
| 2,516
|
0
| 86,299
| 46,892
| 49,832
|
1
| 85,783
| 19,482
| 11,347
|
1
| 90,194
| 10,099
| 477
|
1
| 57,686
| 33,143
| 1,814
|
0
| 61,861
| 54,364
| 35,746
|
0
| 78,005
| 13,687
| 25,123
|
1
| 68,220
| 65,248
| 6,802
|
1
| 81,792
| 28,147
| 10,444
|
0
| 66,590
| 12,833
| 23,703
|
0
| 68,854
| 60,433
| 3,848
|
0
| 87,689
| 1,630
| 40,066
|
1
| 38,499
| 8,965
| 13,046
|
0
| 74,856
| 7,523
| 19,303
|
0
| 75,092
| 19,389
| 33,433
|
1
| 60,494
| 53,608
| 33,158
|
0
| 82,036
| 73,796
| 58,562
|
1
| 55,712
| 392
| 409
|
0
| 74,724
| 47,209
| 29,720
|
1
| 52,064
| 11,105
| 11,878
|
1
| 84,833
| 5,150
| 5,157
|
1
| 84,910
| 1,846
| 35,538
|
0
| 49,624
| 10,355
| 45,183
|
1
| 86,072
| 70,460
| 3,831
|
0
| 87,509
| 1,508
| 10,010
|
0
| 76,824
| 15,783
| 19,734
|
0
| 72,038
| 11,495
| 45,541
|
0
| 85,911
| 85,939
| 20,046
|
1
| 78,559
| 68,148
| 14,525
|
0
| 77,375
| 1,678
| 47,379
|
0
| 54,423
| 653
| 21,760
|
0
| 90,077
| 23,748
| 6,355
|
0
| 68,854
| 69,666
| 36,331
|
1
| 64,128
| 20,609
| 13,481
|
1
| 87,906
| 16,842
| 2,012
|
0
| 72,038
| 10,099
| 33,513
|
0
| 75,774
| 5,573
| 15,708
|
1
| 86,940
| 36,699
| 1,898
|
1
| 78,559
| 13,577
| 3,302
|
0
| 87,742
| 30,648
| 60,288
|
1
| 62,154
| 60,463
| 914
|
1
| 76,877
| 33,569
| 3,885
|
0
| 68,854
| 22,624
| 9,140
|
1
| 66,779
| 10,099
| 477
|
1
| 59,709
| 59,917
| 8,534
|
0
| 64,920
| 7,504
| 55,530
|
0
| 43,874
| 1,052
| 36,230
|
1
| 67,393
| 50,423
| 1,923
|
0
| 49,624
| 12,512
| 13,530
|
1
| 77,567
| 63,583
| 12,223
|
0
| 80,103
| 49,406
| 29,856
|
0
| 62,154
| 3,160
| 28,672
|
0
| 46,657
| 7,537
| 3,166
|
1
| 63,329
| 1,508
| 4,553
|
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MovielensLatest_x1
The MovieLens dataset consists of users' tagging records on movies. The task is formulated as personalized tag recommendation with each tagging record (user_id, item_id, tag_id) as an data instance. The target value denotes whether the user has assigned a particular tag to the movie. We provide the reusable, processed dataset released by the BARS benchmark, which are randomly split into 7:2:1 as the training set, validation set, and test set, respectively.
Dataset Details
Repository: https://github.com/reczoo/BARS/blob/main/datasets/MovieLens/README.md#movielenslatest_x1
Used by papers:
- 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.
- Weiyu Cheng, Yanyan Shen, Linpeng Huang. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In AAAI 2020.
Check the md5sum for data integrity:
```bash $ md5sum train.csv valid.csv test.csv efc8bceeaa0e895d566470fc99f3f271 train.csv e1930223a5026e910ed5a48687de8af1 valid.csv 54e8c6baff2e059fe067fb9b69e692d0 test.csv ```
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