Ontology Learning Through Focused Crawling and Information Extraction

Ontology Learning Through Focused Crawling and Information Extraction. Luong, H., P., Gauch, S., & Wang, Q. In 2009 International Conference on Knowledge and Systems Engineering, pages 106-112, 2009. Ieee.

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Ontology learning aims to facilitate the construction of ontologies by decreasing the amount of effort required to produce an ontology for a new domain. However, there are few studies that attempt to automate the entire ontology learning process from the collection of domain-specific literature, to text mining to build new ontologies or enrich existing ones. In this paper, we present a complete framework for ontology learning that enables us to retrieve documents from the Web using focused crawling, and then use a SVM (support vector machine) classifier to identify domain-specific documents and perform text mining in order to extract useful information for the ontology enrichment process. We have carried out several experiments on components of this framework in a biological domain, amphibian morphology. This paper reports on the overall system architecture and our initial experiments on information extraction using text mining techniques to enrich the domain ontology.

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 bibtype = {inProceedings},
 author = {Luong, Hiep Phuc and Gauch, Susan and Wang, Qiang},
 booktitle = {2009 International Conference on Knowledge and Systems Engineering}
}

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