Clustering Information Retrieval Search Outputs

Abstract

Users are known to experience difficulties in dealing with information retrieval search outputs, especially if those outputs are above a certain size. It has been argued by several researchers that search output clustering can help users in their interaction with IR systems in some retrieval situations, providing them with an overview of their results by exploiting the topicality information that resides in the output but has not been used at the retrieval stage. This overview might enable them to find relevant documents more easily by focusing on the most promising clusters, or to use the clusters as a starting-point for query refinement or expansion. In this paper, the results of experiments carried out to assess the viability of clustering as a search output presentation method are reported and discussed.

Contributors

Yasemin Kural

Steve Robertson

Susan Jones

Conference

Publication date: April 1999

Publication date (Print): April 1999

Pages: 1-9

Affiliations

School of Informatics, City University

Article

DOI: 10.14236/ewic/IRSG1999.9

Copyright statement: © Yasemin Kural et al. Published by BCS Learning and Development Ltd. 21st Annual BCS-IRSG Colloquium on IR, Glasgow

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: 21st Annual BCS-IRSG Colloquium on IR

Conference acronym: IRSG

Conference number: 21

Conference location: Glasgow

Conference date: 19-20 April 1999

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: IR Research

Product

Product Information: 1477-9358BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/IRSG1999.9

Self URI (journal page): https://ewic.bcs.org/

Categories

Series title: Electronic Workshops in Computing