Online Query Refinement on Information Retrieval Systems: A Process Model of Searched System Interactions

Artificial Intelligence Lab, Department of MIS, University of Arizona === This article reports findings of empirical research that investigated information searchers online query refinement process. Prior studies have recognized the information specialists' role in helping searchers articulate...

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Bibliographic Details
Main Authors: Chen, Hsinchun, Dhar, Vasant
Language:en
Published: ACM 1990
Subjects:
Online Access:http://hdl.handle.net/10150/105597
Description
Summary:Artificial Intelligence Lab, Department of MIS, University of Arizona === This article reports findings of empirical research that investigated information searchers online query refinement process. Prior studies have recognized the information specialists' role in helping searchers articulate and refine queries. Using a semantic network and a Problem Behavior Graph to represent the online search our study revealed that searchers also refined their own queries in an online task environment. The information retrieval system played a passive role in assisting online query refinement, which was, however, one that confirmed Taylor's four-level query formulation model. Based on our empirical findings, we proposed using process model to facilitate and improve query refinement in an online environment. We believe incorporating this model into retrieval systems can result in the design of more "intelligent" and useful information retrieval systems.