Ontology Learning Through Focused Crawling and Information Extraction
Hiep Phuc Luong, Susan Gauch, Qiang Wang · 2009
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.