18 citations · 97 across the 27 of their papers we have counts for
6 papers · 1 filter
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search
Jianghong Zhou, Eugene Agichtein
To support complex search tasks, where the initial information requirements are complex or may change during the search, a search engine must adapt the information delivery as the…
Diversifying Multi-aspect Search Results Using Simpson's Diversity Index
Jianghong Zhou, Eugene Agichtein, Surya Kallumadi
In search and recommendation, diversifying the multi-aspect search results could help with reducing redundancy, and promoting results that might not be shown otherwise. Many previo…
De-Biased Modelling of Search Click Behavior with Reinforcement Learning
Jianghong Zhou, Sayyed M. Zahiri, Simon Hughes +3
Users' clicks on Web search results are one of the key signals for evaluating and improving web search quality and have been widely used as part of current state-of-the-art Learnin…
DeepCAT: Deep Category Representation for Query Understanding in E-commerce Search
Ali Ahmadvand, Surya Kallumadi, Faizan Javed +1
Mapping a search query to a set of relevant categories in the product taxonomy is a significant challenge in e-commerce search for two reasons: 1) Training data exhibits severe cla…
APRF-Net: Attentive Pseudo-Relevance Feedback Network for Query Categorization
Ali Ahmadvand, Sayyed M. Zahiri, Simon Hughes +3
Query categorization is an essential part of query intent understanding in e-commerce search. A common query categorization task is to select the relevant fine-grained product cate…
Identifying Helpful Sentences in Product Reviews
Iftah Gamzu, Hila Gonen, Gilad Kutiel +2
In recent years online shopping has gained momentum and became an important venue for customers wishing to save time and simplify their shopping process. A key advantage of shoppin…