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Extracting ontology concept hierarchies from text using Markov logic

Published:22 March 2010Publication History

ABSTRACT

Ontologies have proven to be a powerful tool for many tasks such as natural language processing and information filtering and retrieval. However their development is an error prone and expensive task. One approach for this problem is to provide automatic or semi-automatic support for ontology construction. This work presents the Probabilistic Relational Hierarchy Extraction (PREHE) technique, an approach for extracting concept hierarchies from text that uses statistical relational learning and natural language processing for combining cues from many state-of-the-art techniques. A Markov Logic Network has been developed for this task and is described here. A preliminary evaluation of the proposed approach is also outlined.

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      cover image ACM Conferences
      SAC '10: Proceedings of the 2010 ACM Symposium on Applied Computing
      March 2010
      2712 pages
      ISBN:9781605586397
      DOI:10.1145/1774088

      Copyright © 2010 ACM

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      Publication History

      • Published: 22 March 2010

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      SAC '10 Paper Acceptance Rate364of1,353submissions,27%Overall Acceptance Rate1,650of6,669submissions,25%

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