PrOntoLearn: Unsupervised lexico-semantic ontology generation using probabilistic methods

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

2 Scopus citations

Abstract

It is well known that manually formalizing a domain is a tedious and cumbersome process. It is constrained by the knowledge acquisition bottleneck. Therefore, many researchers have developed algorithms and systems to help automate the process. Among them are systems that incorporate text corpora in the knowledge acquisition process. Here, we provide a novel method for unsupervised bottom-up ontology generation. It is based on lexico-semantic structures and Bayesian reasoning to expedite the ontology generation process. To illustrate our approach, we provide three examples generating ontologies in diverse domains and validate them using qualitative and quantitative measures. The examples include the description of high-throughput screening data relevant to drug discovery and two custom text corpora. Our unsupervised method produces viable results with sometimes unexpected content. It is complementary to the typical top-down ontology development process. Our approach may therefore also be useful to domain experts.

Original languageEnglish (US)
Title of host publicationUncertainty Reasoning for the Semantic Web II - International Workshops, URSW 2008-2010 Held at ISWC and UniDL 2010 Held at FLoC, Revised Selected Papers
Pages217-236
Number of pages20
DOIs
StatePublished - Jan 30 2013
Event6th International Workshop on Uncertainty Reasoning for the Semantic Web, URSW 2010, Held as Part of the 9th International Semantic Web Conferences, ISWC 2010 and 1st International Workshop on Uncertainty in Description Logics, UniDL2010 - Shanghai, China
Duration: Nov 7 2010Nov 7 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7123 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Workshop on Uncertainty Reasoning for the Semantic Web, URSW 2010, Held as Part of the 9th International Semantic Web Conferences, ISWC 2010 and 1st International Workshop on Uncertainty in Description Logics, UniDL2010
CountryChina
CityShanghai
Period11/7/1011/7/10

Keywords

  • Ontology Learning
  • Ontology Modeling
  • Probabilistic Methods

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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    Abeyruwan, S., Visser, U., Lemmon, V., & Schürer, S. (2013). PrOntoLearn: Unsupervised lexico-semantic ontology generation using probabilistic methods. In Uncertainty Reasoning for the Semantic Web II - International Workshops, URSW 2008-2010 Held at ISWC and UniDL 2010 Held at FLoC, Revised Selected Papers (pp. 217-236). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7123 LNAI). https://doi.org/10.1007/978-3-642-35975-0-12