Taxonomy construction using compound similarity measure

Mahmood Neshati, Leila Sharif Hassanabadi

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 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 publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages915-932
Number of pages18
Volume4803 LNCS
EditionPART 1
Publication statusPublished - 1 Dec 2007
EventOTM Confederated International Conferences CoopIS, DOA, ODBASE, GADA, and IS 2007 - Vilamoura
Duration: 25 Nov 200730 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4803 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherOTM Confederated International Conferences CoopIS, DOA, ODBASE, GADA, and IS 2007
CityVilamoura
Period25/11/0730/11/07

Fingerprint

Taxonomies
Taxonomy
Similarity Measure
Learning
Ontology Learning
Neural Networks (Computer)
Syntactics
Learning Process
Neural Network Model
Ontology
Research Personnel
Neural networks
Similarity
Knowledge

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Neshati, M., & Hassanabadi, L. S. (2007). Taxonomy construction using compound similarity measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 4803 LNCS, pp. 915-932). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4803 LNCS, No. PART 1).

Taxonomy construction using compound similarity measure. / Neshati, Mahmood; Hassanabadi, Leila Sharif.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4803 LNCS PART 1. ed. 2007. p. 915-932 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4803 LNCS, No. PART 1).

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

Neshati, M & Hassanabadi, LS 2007, Taxonomy construction using compound similarity measure. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 4803 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4803 LNCS, pp. 915-932, OTM Confederated International Conferences CoopIS, DOA, ODBASE, GADA, and IS 2007, Vilamoura, 25/11/07.
Neshati M, Hassanabadi LS. Taxonomy construction using compound similarity measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 4803 LNCS. 2007. p. 915-932. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
Neshati, Mahmood ; Hassanabadi, Leila Sharif. / Taxonomy construction using compound similarity measure. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4803 LNCS PART 1. ed. 2007. pp. 915-932 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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