| Convolutional matrix factorization for document context-aware recommendation D Kim, C Park, J Oh, S Lee, H Yu Proceedings of the 10th ACM conference on recommender systems, 233-240, 2016 | 720 | 2016 |
| Protecting location privacy using location semantics B Lee, J Oh, H Yu, J Kim Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 143 | 2011 |
| Deep hybrid recommender systems via exploiting document context and statistics of items D Kim, C Park, J Oh, H Yu Information Sciences 417, 72-87, 2017 | 105 | 2017 |
| Novel recommendation based on personal popularity tendency J Oh, S Park, H Yu, M Song, ST Park 2011 IEEE 11th international conference on data mining, 507-516, 2011 | 92 | 2011 |
| Improving top-K recommendation with truster and trustee relationship in user trust network C Park, D Kim, J Oh, H Yu Information Sciences 374, 100-114, 2016 | 54 | 2016 |
| Fast and robust parallel SGD matrix factorization J Oh, WS Han, H Yu, X Jiang Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 49 | 2015 |
| S-hot: Scalable high-order tucker decomposition J Oh, K Shin, EE Papalexakis, C Faloutsos, H Yu Proceedings of the Tenth ACM International Conference on Web Search and Data …, 2017 | 48 | 2017 |
| Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS H Yu, T Kim, J Oh, I Ko, S Kim, WS Han Proceedings of the third international workshop on Data and text mining in …, 2009 | 48 | 2009 |
| When to recommend: A new issue on TV show recommendation J Oh, S Kim, J Kim, H Yu Information Sciences 280, 261-274, 2014 | 47 | 2014 |
| Do" also-viewed" products help user rating prediction? C Park, D Kim, J Oh, H Yu Proceedings of the 26th International Conference on World Wide Web, 1113-1122, 2017 | 42 | 2017 |
| RecTime: Real-time recommender system for online broadcasting Y Park, J Oh, H Yu Information Sciences 409, 1-16, 2017 | 37 | 2017 |
| Time-dependent user profiling for TV recommendation J Oh, Y Sung, J Kim, M Humayoun, YH Park, H Yu 2012 Second International Conference on Cloud and Green Computing, 783-787, 2012 | 26 | 2012 |
| Scalable and parallelizable influence maximization with random walk ranking and rank merge pruning S Kim, D Kim, J Oh, JH Hwang, WS Han, W Chen, H Yu Information Sciences 415, 171-189, 2017 | 25 | 2017 |
| Efficient feature weighting methods for ranking H Yu, J Oh, WS Han Proceedings of the 18th acm conference on information and knowledge …, 2009 | 25 | 2009 |
| Influence maximization based on reachability sketches in dynamic graphs D Kim, D Hyeon, J Oh, WS Han, H Yu Information Sciences 394, 217-231, 2017 | 22 | 2017 |
| Tri-fly: Distributed estimation of global and local triangle counts in graph streams K Shin, M Hammoud, E Lee, J Oh, C Faloutsos Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia …, 2018 | 20 | 2018 |
| Processing time-dependent shortest path queries without pre-computed speed information on road networks J Kim, WS Han, J Oh, S Kim, H Yu Information sciences 255, 135-154, 2014 | 20 | 2014 |
| Trecso: Enhancing top-k recommendation with social information C Park, D Kim, J Oh, H Yu Proceedings of the 25th International Conference Companion on World Wide Web …, 2016 | 18 | 2016 |
| RefMed: relevance feedback retrieval system fo PubMed H Yu, T Kim, J Oh, I Ko, S Kim Proceedings of the 18th ACM conference on Information and knowledge …, 2009 | 15 | 2009 |
| Predicting user purchase in e-commerce by comprehensive feature engineering and decision boundary focused under-sampling C Park, D Kim, J Oh, H Yu Proceedings of the 2015 International ACM Recommender Systems Challenge, 1-4, 2015 | 13 | 2015 |
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