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8 papers · 2 filters
Sampling-Decomposable Generative Adversarial Recommender
Binbin Jin, Defu Lian, Zheng Liu +4
Recommendation techniques are important approaches for alleviating information overload. Being often trained on implicit user feedback, many recommenders suffer from the sparsity c…
Embedding-based Retrieval in Facebook Search
Jui-Ting Huang, Ashish Sharma, Shuying Sun +6
Search in social networks such as Facebook poses different challenges than in classical web search: besides the query text, it is important to take into account the searcher's cont…
Proceedings of the KG-BIAS Workshop 2020 at AKBC 2020
Edgar Meij, Tara Safavi, Chenyan Xiong +3
The KG-BIAS 2020 workshop touches on biases and how they surface in knowledge graphs (KGs), biases in the source data that is used to create KGs, methods for measuring or remediati…
MIMICS: A Large-Scale Data Collection for Search Clarification
Hamed Zamani, Gord Lueck, Everest Chen +3
Search clarification has recently attracted much attention due to its applications in search engines. It has also been recognized as a major component in conversational information…
Guided Transformer: Leveraging Multiple External Sources for Representation Learning in Conversational Search
Helia Hashemi, Hamed Zamani, W. Bruce Croft
Asking clarifying questions in response to ambiguous or faceted queries has been recognized as a useful technique for various information retrieval systems, especially conversation…
Few-Shot Generative Conversational Query Rewriting
Shi Yu, Jiahua Liu, Jingqin Yang +4
Conversational query rewriting aims to reformulate a concise conversational query to a fully specified, context-independent query that can be effectively handled by existing inform…