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This work addresses the problem of effective information seeking for users with low clarity of information need and unfamiliarity with content, offering an alternative to explicit query formulation.
This paper investigates multi-turn information seeking dialogues by observing human participants and analyzing conversation structures. The insights gained were used to develop a prototype system that complements query-based information retrieval, particularly when information needs are unclear or collection familiarity is low.
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.