Relevence Assessment of Topic Ontology

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Author(s)

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Detail(s)

Original languageEnglish
Title of host publicationAdvances in Intelligent IT - Active Media Technology 2006
PublisherIOS Press BV
Pages44-51
Volume138
ISBN (print)1586036157, 9781586036157
Publication statusPublished - 2006

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume138
ISSN (Print)0922-6389

Conference

Title4th International Conference on Active Media Technology, AMT 2006
PlaceAustralia
CityBrisbane
Period7 - 9 June 2006

Abstract

In traditional Information Retrieval (IR), user profiles are often represented by keyword/concepts space vectors or by some predefined categories. Unfortunately, this data is often inadequately or incompletely interpreted. Ontology-based user profile is another newer approach. This method is able to provide richer semantic information to facilitate information retrieval processes. It has become an important means for semantic-based information search and retrieval. Some ontology-based user profile models have been developed over the past few years. With the increasing usage of this method, it raises the issues of effective relevance measurement for the evaluation of ontologies. In practice, it is crucial to find a good relevance assessment algorithm for measuring the quality of ontologies. To represent user profile by relevant topic ontology, this paper presents a new method capable of measuring the user profile more objectively and hence has great potential to enhance the IR processes.

Research Area(s)

  • information retrieval, relevance assessment, topic ontology, user profiles

Bibliographic Note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to lbscholars@cityu.edu.hk.

Citation Format(s)

Relevence Assessment of Topic Ontology. / Zhou, Xujuan; Li, Yuefeng; Xu, Yue et al.
Advances in Intelligent IT - Active Media Technology 2006. Vol. 138 IOS Press BV, 2006. p. 44-51 (Frontiers in Artificial Intelligence and Applications; Vol. 138).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review