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Permanent link (DOI): https://doi.org/10.7939/R3HQ14

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Text Document Topical Recursive Clustering and Automatic Labeling of a Hierarchy of Document Clusters Open Access

Descriptions

Other title
Subject/Keyword
Cluster Labeling
Automatic Taxonomy Generation
Search Result Clustering
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Li, Xiaoxiao
Supervisor and department
Zaiane, Osmar (Computing Science)
Examining committee member and department
Zaiane, Osmar (Computing Science)
Lin, Guohui (Computing Science)
Rathi, Dinesh (Library and Information Studies)
Department
Department of Computing Science
Specialization

Date accepted
2012-09-28T08:13:12Z
Graduation date
2012-09
Degree
Master of Science
Degree level
Master's
Abstract
The overwhelming amount of textual documents currently available highlights the need for information organization and discovery. Effectively organizing documents into a hierarchy of topics and subtopics makes it easier for users to browse the documents. This thesis borrows community mining techniques from social network analysis to generate a hierarchy of topically coherent document clusters. It focuses on giving the document clusters descriptive labels. We propose to use different centrality measures in networks of co-occurring terms to label the document clusters. We also incorporate keyphrase extraction and automatic titling in cluster labeling. The results show that the cluster labeling method utilizing KEA to extract keyphrases from the documents generates the best labels overall comparing to other methods and baselines. We also built an interactive browsing web interface for users to examine the taxonomies.
Language
English
DOI
doi:10.7939/R3HQ14
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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