Towards auto-construction of domain ontology: An auto-constructed domain conceptual lexicon and its application to extractive summarization

Hsun Hui Huang, Yau-Hwang Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A domain conceptual lexicon can be used for the construction of a domain ontology. In this paper, a method of auto-constructing a domain conceptual lexicon is proposed. The conceptual lexicon is represented by WordNet senses and their relations. Using the domain conceptual lexicon, an extractive summarization method is proposed. A characteristic of the scheme is that each sentence of a document is represented by a set of WordNet senses and constitutes a fuzzy transaction for mining conceptual lexicon and ranking relevance. A prototype of this automatic text summarization scheme is built and an intrinsic method with the information-retrieval criteria is used for measuring the summary quality.

Original languageEnglish
Title of host publicationProceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Pages2947-2952
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
Event6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 - Hong Kong, China
Duration: 2007 Aug 192007 Aug 22

Publication series

NameProceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Volume5

Other

Other6th International Conference on Machine Learning and Cybernetics, ICMLC 2007
CountryChina
CityHong Kong
Period07-08-1907-08-22

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Software
  • Theoretical Computer Science

Cite this

Huang, H. H., & Kuo, Y-H. (2007). Towards auto-construction of domain ontology: An auto-constructed domain conceptual lexicon and its application to extractive summarization. In Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007 (pp. 2947-2952). [4370652] (Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007; Vol. 5). https://doi.org/10.1109/ICMLC.2007.4370652