An Approach Towards Self-Supervised Classification Using Cyc

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Due to the long duration required to perform manual knowledge entry by human knowledge engineers it is desirable to find methods to automatically acquire knowledge about the world by accessing online information. In this work I examine using the Cyc ontology to guide the creation of Naïve Bayes classifiers to provide knowledge about items described in Wikipedia articles. Given an initial set of Wikipedia articles the system uses the ontology to create positive and negative training sets for the classifiers in each category. The order in which classifiers are generated and used to test articles is also guided by the ... continued below

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Coursey, Kino High December 2006.

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  • Coursey, Kino High

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Description

Due to the long duration required to perform manual knowledge entry by human knowledge engineers it is desirable to find methods to automatically acquire knowledge about the world by accessing online information. In this work I examine using the Cyc ontology to guide the creation of Naïve Bayes classifiers to provide knowledge about items described in Wikipedia articles. Given an initial set of Wikipedia articles the system uses the ontology to create positive and negative training sets for the classifiers in each category. The order in which classifiers are generated and used to test articles is also guided by the ontology. The research conducted shows that a system can be created that utilizes statistical text classification methods to extract information from an ad-hoc generated information source like Wikipedia for use in a formal semantic ontology like Cyc. Benefits and limitations of the system are discussed along with future work.

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  • December 2006

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  • May 5, 2008, 3:02 p.m.

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  • Jan. 21, 2014, 1:40 p.m.

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Citations, Rights, Re-Use

Coursey, Kino High. An Approach Towards Self-Supervised Classification Using Cyc, thesis, December 2006; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc5470/: accessed March 26, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .