Semi-automatic construction of topic ontologies
EWMF'05/KDO'05 Proceedings of the 2005 joint international conference on Semantics, Web and Mining
Improving portuguese term extraction
PROPOR'12 Proceedings of the 10th international conference on Computational Processing of the Portuguese Language
Bridging concept identification for constructing information networks from text documents
Bisociative Knowledge Discovery
Domain taxonomy learning from text: The subsumption method versus hierarchical clustering
Data & Knowledge Engineering
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This paper presents a novel methodology for topic ontology learning from text documents. The proposed methodology, named OntoTermExtraction (Term Extraction for Ontology learning), is based on OntoGen, a semi-automated tool for topic ontology construction, upgraded by using an advanced terminology extraction tool in an iterative, semi-automated ontology construction process. This process consists of (a) document clustering to find the nodes in the topic ontology, (b) term extraction from document clusters, (c) populating the term vocabulary and keyword extraction, and (d) choosing the concept names by comparing the best-ranked terms with the extracted keywords. The approach was successfully used for generating the ontology of topics in Inductive Logic Programming, learned semi-automatically from papers indexed in the ILPnet2 publications database.