Taxonomy learning using compound similarity measure

Mahmood Neshati, Ali Alijamaat, Hassan Abolhassani, Afshin Rahimi, Mehdi Hoseini

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

12 Citations (Scopus)

Abstract

Taxonomy learning is one of the major steps in ontology learning process. Manual construction of taxonomies is a time-consuming and cumbersome task. Recently many researchers have focused on automatic taxonomy learning, but still quality of generated taxonomies is not satisfactory. In this paper we have proposed a new compound similarity measure. This measure is based on both knowledge poor and knowledge rich approaches to find word similarity. We also used Machine Learning Technique (Neural Network model) for combination of several similarity methods. We have compared our method with simple syntactic similarity measure. Our measure considerably improves the precision and recall of automatic generated taxonomies.

Original languageEnglish
Title of host publicationProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Pages487-490
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2007
EventIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 - Silicon Valley, CA, United States
Duration: 2 Nov 20075 Nov 2007

Publication series

NameProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007

Conference

ConferenceIEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
CountryUnited States
CitySilicon Valley, CA
Period2/11/075/11/07

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications

Cite this

Neshati, M., Alijamaat, A., Abolhassani, H., Rahimi, A., & Hoseini, M. (2007). Taxonomy learning using compound similarity measure. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007 (pp. 487-490). [4427141] (Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007). https://doi.org/10.1109/WI.2007.99