44 citations · 127 across the 14 of their papers we have counts for
10 papers · 1 filter
Disentangled Representation for Diversified Recommendations
Xiaoying Zhang, Hongning Wang, Hang Li
Accuracy and diversity have long been considered to be two conflicting goals for recommendations. We point out, however, that as the diversity is typically measured by certain pre-…
Graph-based Extractive Explainer for Recommendations
Peng Wang, Renqin Cai, Hongning Wang
Explanations in a recommender system assist users in making informed decisions among a set of recommended items. Great research attention has been devoted to generating natural lan…
Explanation as a Defense of Recommendation
Aobo Yang, Nan Wang, Hongbo Deng +1
Textual explanations have proved to help improve user satisfaction on machine-made recommendations. However, current mainstream solutions loosely connect the learning of explanatio…
Directional Multivariate Ranking
Nan Wang, Hongning Wang
User-provided multi-aspect evaluations manifest users' detailed feedback on the recommended items and enable fine-grained understanding of their preferences. Extensive studies have…
Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation
Jibang Wu, Renqin Cai, Hongning Wang
Predicting users' preferences based on their sequential behaviors in history is challenging and crucial for modern recommender systems. Most existing sequential recommendation algo…
Context Attentive Document Ranking and Query Suggestion
Wasi Uddin Ahmad, Kai-Wei Chang, Hongning Wang
We present a context-aware neural ranking model to exploit users' on-task search activities and enhance retrieval performance. In particular, a two-level hierarchical recurrent neu…