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RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search., and . WWW, page 2842-2848. ACM / IW3C2, (2020)Generating and Validating Contextually Relevant Justifications for Conversational Recommendation., , , and . CHIIR, page 284-289. ACM, (2022)Modeling Answerer Behavior in Collaborative Question Answering Systems., and . ECIR, volume 6611 of Lecture Notes in Computer Science, page 67-79. Springer, (2011)Searching for Products in Virtual Reality: Understanding the Impact of Context and Result Presentation on User Experience., , , , , and . SIGIR, page 2359-2363. ACM, (2023)Quantifying the Effects of Prosody Modulation on User Engagement and Satisfaction in Conversational Systems., and . CHIIR, page 417-421. ACM, (2020)The conference was cancelled due to the international COVID-19 health crisis..Would you Like to Talk about Sports Now?: Towards Contextual Topic Suggestion for Open-Domain Conversational Agents., , and . CHIIR, page 83-92. ACM, (2020)The conference was cancelled due to the international COVID-19 health crisis..RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search., and . CoRR, (2021)Trust, but verify: predicting contribution quality for knowledge base construction and curation., , , and . WSDM, page 553-562. ACM, (2014)ViewSer: enabling large-scale remote user studies of web search examination and interaction., and . SIGIR, page 365-374. ACM, (2011)Combining Lexical, Syntactic, and Semantic Evidence for Textual Entailment Classification., , and . TAC, NIST, (2008)