Conference proceeding
Dynamicity vs. Effectiveness: Studying Online Clustering for Scatter/Gather
PROCEEDINGS 32ND ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, pp 19-26
01 Jan 2009
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We proposed and implemented a novel clustering algorithm called LAIR,2, which has constant running time average for on-the-fly Scatter/Gather browsing [4]. Our experiments showed that when running on a single processor, the LAIR2 on-line clustering algorithm was several hundred times faster than a parallel Buckshot algorithm running on multiple processors [11]. This paper reports on a study that examined the effectiveness of the LAIR2 algorithm in terms of clustering quality and its impact on retrieval performance. We conducted a user study on 24 subjects to evaluate on-the-fly LAIR2 clustering in Scatter/Gather search tasks by comparing its performance to the Buckshot algorithm, a classic method for Scatter/Gather browsing [4]. Results showed significant differences in terms of subjective perceptions of clustering quality. Subjects perceived that the LAIR2 algorithm produced significantly better quality clusters than the Buckshot method did. Subjects felt that it took less effort to complete the tasks with the LAIR2 system, which was more effective in helping them in the tasks. Interesting patterns also emerged from subjects' comments in the final open-ended questionnaire. We discuss implications and future research.
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Details
- Title
- Dynamicity vs. Effectiveness: Studying Online Clustering for Scatter/Gather
- Creators
- Weimao Ke - University of North Carolina at Chapel HillCassidy R. Sugimoto - University of North Carolina at Chapel HillJaved Mostafa - University of North Carolina at Chapel Hill
- Contributors
- M Sanderson (Editor)C X Zhai (Editor)J Zobel (Editor)J Allan (Editor)J A Aslam (Editor)
- Publication Details
- PROCEEDINGS 32ND ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, pp 19-26
- Publisher
- Assoc Computing Machinery
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000270976500004
- Scopus ID
- 2-s2.0-72449142736
- Other Identifier
- 991020546585104721
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Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Theory & Methods