8 citations · 9 across the 2 of their papers we have counts for
5 papers · 1 filter
MLLMRec: A Preference Reasoning Paradigm with Graph Refinement for Multimodal Recommendation
Yuzhuo Dang, Xin Zhang, Zhiqiang Pan +4
Multimodal recommendation combines the user historical behaviors with the modal features of items to capture the tangible user preferences, presenting superior performance compared…
Attribute-aware Diversification for Sequential Recommendations
Anton Steenvoorden, Emanuele Di Gloria, Wanyu Chen +2
Users prefer diverse recommendations over homogeneous ones. However, most previous work on Sequential Recommenders does not consider diversity, and strives for maximum accuracy, re…
Improving End-to-End Sequential Recommendations with Intent-aware Diversification
Wanyu Chen, Pengjie Ren, Fei Cai +1
Sequential Recommendation (SRs) that capture users' dynamic intents by modeling user sequential behaviors can recommend closely accurate products to users. Previous work on SRs is…
Joint Neural Collaborative Filtering for Recommender Systems
Wanyu Chen, Fei Cai, Honghui Chen +1
We propose a J-NCF method for recommender systems. The J-NCF model applies a joint neural network that couples deep feature learning and deep interaction modeling with a rating mat…
Attention-based Hierarchical Neural Query Suggestion
Wanyu Chen, Fei Cai, Honghui Chen +1
Query suggestions help users of a search engine to refine their queries. Previous work on query suggestion has mainly focused on incorporating directly observable features such as…