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PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation using Probabilistic Methods

An ontology is a formal, explicit specification of a shared conceptualization. Formalizing an ontology for a domain is a tedious and cumbersome process. It is constrained by the knowledge acquisition bottleneck (KAB). There exists a large number of text corpora that can be used for classification in order to create ontologies with the intention to provide better support for the intended parties. In our research we provide a novel unsupervised bottom-up ontology generation method. This method is based on lexico-semantic structures and Bayesian reasoning to expedite the ontology generation process. This process also provides evidence to domain experts to build ontologies based on top-down approaches.
Date01 January 2010
CreatorsAbeyruwan, Saminda Wishwajith
PublisherScholarly Repository
Source SetsUniversity of Miami
Detected LanguageEnglish
SourceOpen Access Theses

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