共 50 条
- [41] User Feedback-Based Counterfactual Data Augmentation for Sequential Recommendation KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, PT III, KSEM 2023, 2023, 14119 : 370 - 382
- [42] Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors KDD '21: PROCEEDINGS OF THE 27TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2021, : 3002 - 3010
- [43] Collaborative Filtering by Sequential Extraction of User-Item Clusters Based on Structural Balancing Approach 2009 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3, 2009, : 1540 - 1545
- [44] KEP-Rec: A Knowledge Enhanced User-Item Relation Prediction Model for Personalized Recommendation WEB AND BIG DATA, PT II, APWEB-WAIM 2022, 2023, 13422 : 239 - 254
- [46] Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2019, : 1373 - 1379
- [48] entity2rec: Learning User-Item Relatedness from Knowledge Graphs for Top-N Item Recommendation PROCEEDINGS OF THE ELEVENTH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS'17), 2017, : 32 - 36
- [49] Recursive RNN Based Shift Representation Learning for Dynamic User-Item Interaction Prediction ADVANCED DATA MINING AND APPLICATIONS, 2020, 12447 : 379 - 394