Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites (2004)
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| Venue: | COMPUTATIONAL LINGUISTICS |
| Citations: | 66 - 19 self |
BibTeX
@ARTICLE{Navigli04learningdomain,
author = {Roberto Navigli and Paola Velardi},
title = {Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites },
journal = {COMPUTATIONAL LINGUISTICS},
year = {2004},
volume = {30},
pages = {2004}
}
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Abstract
We present a method and a tool, OntoLearn, aimed at the extraction of domain ontologies from web sites, and more generally from documents shared among the members of virtual organizations. OntoLearn first extracts a domain terminology from available documents. Then, complex domain terms are semantically interpreted and arranged in a hierarchical fashion. Finally, a general purpose ontology, i.e. WordNet, is trimmed and enriched with the detected domain concepts. The major novel aspect of this approach is semantic interpretation, that is, the association of a complex concept with a complex term. This involves finding the appropriate WordNet concept for each word of a terminological string and the appropriate conceptual relations that hold among the concept components. Semantic interpretation is based on a new WSD algorithm, called structural semantic interconnections.







