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Title: Analyzing and Characterizing User Intent in Information-seeking Conversations
Understanding and characterizing how people interact in information-seeking conversations will be a crucial component in developing effective conversational search systems. In this paper, we introduce a new dataset designed for this purpose and use it to analyze information-seeking conversations by user intent distribution, co-occurrence, and flow patterns. The MSDialog dataset is a labeled conversation dataset of question answering (QA) interactions between information seekers and providers from an online forum on Microsoft products. The dataset contains more than 2,000 multi-turn QA dialogs with 10,000 utterances that are annotated with user intents on the utterance level. Annotations were done using crowdsourcing. With MSDialog, we find some highly recurring patterns in user intent during an information-seeking process. They could be useful for designing conversational search systems. We will make our dataset freely available to encourage exploration of information-seeking conversation models.  more » « less
Award ID(s):
1715095
NSF-PAR ID:
10090129
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Proceedings of the 41st International ACM SIGIR Conference onResearch and Development in Information Retrieval
Page Range / eLocation ID:
989 to 992
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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