Slicing and dicing the information space using local contexts

Joho, H. and Jose, J.M. (2006) Slicing and dicing the information space using local contexts. In: 1st International Conference on Information Interaction in Context, Copenhagen, Denmark, 18-20 October 2006, pp. 66-74. ISBN 1595934820 (doi: 10.1145/1164820.1164836)

Abstract

In recent years there has been growing interest in faceted grouping of documents for Interactive Information Retrieval (IIR). It is suggested that faceted grouping can offer a flexible way of browsing a collection compared to clustering. However, the success of faceted grouping seems to rely on sufficient knowledge of collection structure. In this paper we propose an approach based on the local contexts of query terms, which is inspired by the interaction of faceted search and browsing. The use of local contexts is appealing since it requires less knowledge of the collection than existing approaches. A task-based user study was carried out to investigate the effectiveness of our interface in varied complexity. The results suggest that the local contexts can be exploited as the source of search result browsing in IIR, and that our interface appears to facilitate different aspects of search process over the task complexity. The implication of the evaluation methodology using high complexity tasks is also discussed.

• Item Type: Conference Proceedings
• Additional Information: © ACM, 2006. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM International Conference Proceeding Series; Vol. 176 http://doi.acm.org/10.1145/1164820.1164836
• Keywords: Documentation, Experimentation, Human Factors
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Joho, Mr Hideo
• Authors: Joho, H., and Jose, J.M.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: ACM Press
• ISBN: 1595934820
• Copyright Holders: Copyright © 2006 ACM Press
• First Published: First published in Proceedings of the 1st International Conference on Information Interaction in Context
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher including additional information statement.

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
39116	1	Adaptive search models for information retrieval	Joemon Jose	Engineering & Physical Sciences Research Council (EPSRC)	EP/C004108/1	Computing Science