855 citations · 2.9k across the 51 of their papers we have counts for
15 papers · 1 filter
Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching
Chen Qu, Feng Ji, Minghui Qiu +5
Deep text matching approaches have been widely studied for many applications including question answering and information retrieval systems. To deal with a domain that has insuffic…
Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match
Keping Bi, Qingyao Ai, W. Bruce Croft
Relevance feedback techniques assume that users provide relevance judgments for the top k (usually 10) documents and then re-rank using a new query model based on those judgments.…
Revisiting Iterative Relevance Feedback for Document and Passage Retrieval
Keping Bi, Qingyao Ai, W. Bruce Croft
As more and more search traffic comes from mobile phones, intelligent assistants, and smart-home devices, new challenges (e.g., limited presentation space) and opportunities come u…
Joint Modeling and Optimization of Search and Recommendation
Hamed Zamani, W. Bruce Croft
Despite the somewhat different techniques used in developing search engines and recommender systems, they both follow the same goal: helping people to get the information they need…
Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce
Minghui Qiu, Liu Yang, Feng Ji +6
Building multi-turn information-seeking conversation systems is an important and challenging research topic. Although several advanced neural text matching models have been propose…
Towards Theoretical Understanding of Weak Supervision for Information Retrieval
Hamed Zamani, W. Bruce Croft
Neural network approaches have recently shown to be effective in several information retrieval (IR) tasks. However, neural approaches often require large volumes of training data t…