Collaborative exploratory search in real-world context

Authors:
Naoki Tani;Danushka Bollegala;Naiwala Chandrasiri;Keisuke Okamoto;Kazunari Nawa;Shuhei Iitsuka;Yutaka Matsuo
Affiliations:
The University of Tokyo, Tokyo, Japan;The University of Tokyo, Tokyo, Japan;Toyota Info Technology Center, Tokyo, Japan;Toyota Motor Corp., Tokyo, Japan;Toyota InfoTechnology Center, Tokyo, Japan;The University of Tokyo, Tokyo, Japan;The University of Tokyo, Tokyo, Japan
Venue:
Proceedings of the 20th ACM international conference on Information and knowledge management
Year:
2011

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Abstract

We propose Collaborative Exploratory Search (CES), which is an integration of dialog analysis and web search that involves multiparty collaboration to accomplish an exploratory information retrieval goal. Given a real-time dialog between users on a single topic; we define CES as the task of automatically detecting the topic of the dialog and retrieving task-relevant web pages to support the dialog. To recognize the task of the dialog, we apply the Author--Topic model as a topic model. Then, attribute extraction is applied to the dialog to obtain the attributes of the tasks. Finally, a specific search query is generated to identify the task-relevant information. We implement and evaluate the CES system for a commercial in-vehicle conversation. We also develop an iPad application that listens to conversations among users and continuously retrieves relevant web pages. Our experimental results reveal that the proposed method outperforms existing methods, which demonstrates the potential usefulness of collaborative exploratory search with practically usable accuracy levels.