Conversational Browsing
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| Publication date | 07-12-2020 |
| Edition | v1 |
| Publisher | ArXiv |
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| Abstract |
How can we better understand the mechanisms behind multi-turn information seeking dialogues? How can we use these insights to design a dialogue system that does not require explicit query formulation upfront as in question answering? To answer these questions, we collected observations of human participants performing a similar task to obtain inspiration for the system design. Then, we studied the structure of conversations that occurred in these settings and used the resulting insights to develop a grounded theory, design and evaluate a first system prototype. Evaluation results show that our approach is effective and can complement query-based information retrieval approaches. We contribute new insights about information-seeking behavior by analyzing and providing automated support for a type of information-seeking strategy that is effective when the clarity of the information need and familiarity with the collection content are low.
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| Document type | Working paper |
| Language | English |
| Published at | https://arxiv.org/abs/2012.03704 |
| Downloads |
vakulenko-2020-conversational-arxiv
(Submitted manuscript)
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