Introducing Query Expansion Methods for Collaborative Information Retrieval

The accuracy of ad-hoc document retrieval systems has plateaued in the last few years. At DFKI, we are working on so-called collaborative information retrieval (CIR) systems which unobtrusively learn from their users’ search processes. We focus on a restricted setting in CIR in which only old queries and correct answer documents to these queries are available for improving a new query. For this restricted setting we propose new approaches for query expansion procedures. This paper describes query expansion methods to be used in collaborative information retrieval. We define collaborative information retrieval as a task, where an information retrieval system uses information gathered from previous search processes from one or several users to improve retrieval performance for the current user searching for information. We show how collaboration of individual users can improve overall information retrieval performance. Performance in this case is expressed in terms of quality and utility of the retrieved information regardless of specific user groups.

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