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Answer Interaction in Non-factoid Question Answering Systems
2019
Proceedings of the 2019 Conference on Human Information Interaction and Retrieval - CHIIR '19
Information retrieval systems are evolving from document retrieval to answer retrieval. Web search logs provide large amounts of data about how people interact with ranked lists of documents, but very little is known about interaction with answer texts. In this paper, we use Amazon Mechanical Turk to investigate three answer presentation and interaction approaches in a non-factoid question answering setting. We find that people perceive and react to good and bad answers very differently, and
doi:10.1145/3295750.3298946
dblp:conf/chiir/Qu0CSZ19
fatcat:xwmxk4ltv5htbm3775mlg7cydu