2.7k citations · 4.6k across the 53 of their papers we have counts for
9 papers · 1 filter
Supervised Deep Hashing for High-dimensional and Heterogeneous Case-based Reasoning
Qi Zhang, Liang Hu, Chongyang Shi +2
Case-based Reasoning (CBR) on high-dimensional and heterogeneous data is a trending yet challenging and computationally expensive task in the real world. A promising approach is to…
Recurrent Coupled Topic Modeling over Sequential Documents
Jinjin Guo, Longbing Cao, Zhiguo Gong
The abundant sequential documents such as online archival, social media and news feeds are streamingly updated, where each chunk of documents is incorporated with smoothly evolving…
Graph Learning based Recommender Systems: A Review
Shoujin Wang, Liang Hu, Yan Wang +6
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS employ advanced graph learning approaches to model u…
Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting
Longbing Cao
While recommendation plays an increasingly critical role in our living, study, work, and entertainment, the recommendations we receive are often for irrelevant, duplicate, or unint…
Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation
Shoujin Wang, Longbing Cao, Liang Hu +4
A transaction-based recommender system (TBRS) aims to predict the next item by modeling dependencies in transactional data. Generally, two kinds of dependencies considered are intr…
Graph Learning Approaches to Recommender Systems: A Review
Shoujin Wang, Liang Hu, Yan Wang +7
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS mainly employ the advanced graph learning approaches…