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Division of labour and sharing of knowledge for synchronous collaborative information retrieval
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Dissertation
Division of labour and sharing of knowledge for synchronous collaborative information retrieval
2008
Overview
Traditional Information Retrieval (IR) research has focussed on a single user interaction modality, where a user searches to satisfy an information need. Recent advances in web technologies and computer hardware have enabled multiple users to collaborate on many computer-supported tasks; therefore there is an increasing opportunity to support two or more users searching together at the same time in order to satisfy a shared information need, which we refer to as Synchronous Collaborative Information Retrieval. Synchronous Collaborative Information Retrieval (SCIR) represents a significant paradigmatic shift from traditional IR systems. In order to support an effective SCIR search new techniques are required to coordinate usersâ activities.  In this thesis we explore the effectiveness of two techniques on SCIR: division of labour and sharing of knowledge. By implementing an effective division of labour policy the search task can be divided across collaborating searchers, thereby avoiding any duplication of effort across the users. In addition, a sharing of knowledge policy refers to the process of passing relevant information across users, whereby group members can benefit from the discoveries of their collaborators. In order to explore these techniques we simulate two users searching together through an incremental relevance feedback system, whereby the ranked lists of documents returned to each user are modified in order to implement various division of labour and sharing of knowledge policies. In order to populate these simulations we extract data from the logs of interactive text search experiments from previous Text REtrieval Conference (TREC) workshops. These experiments represent the first simulations of SCIR to date and the first use of TREC logs in order to populate simulations.
Publisher
ProQuest Dissertations & Theses
Subject
