211 citations · 276 across the 5 of their papers we have counts for
5 papers
A Model-Agnostic Causal Learning Framework for Recommendation using Search Data
Zihua Si, Xueran Han, Xiao Zhang +4
Machine-learning based recommender systems(RSs) has become an effective means to help people automatically discover their interests. Existing models often represent the rich inform…
Neural Document Expansion with User Feedback
Yue Yin, Chenyan Xiong, Cheng Luo +1
This paper presents a neural document expansion approach (NeuDEF) that enriches document representations for neural ranking models. NeuDEF harvests expansion terms from queries whi…
Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graph
Zhuoren Jiang, Yue Yin, Liangcai Gao +2
While the volume of scholarly publications has increased at a frenetic pace, accessing and consuming the useful candidate papers, in very large digital libraries, is becoming an es…
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data
Nan Wang, Hongning Wang, Yiling Jia +1
Explaining automatically generated recommendations allows users to make more informed and accurate decisions about which results to utilize, and therefore improves their satisfacti…
Preliminary Exploration of Formula Embedding for Mathematical Information Retrieval: can mathematical formulae be embedded like a natural language?
Liangcai Gao, Zhuoren Jiang, Yue Yin +3
While neural network approaches are achieving breakthrough performance in the natural language related fields, there have been few similar attempts at mathematical language related…