A Statistical Corpus-Based Term Extractor
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Research on Method of Extracting Chinese Domain Terms Based on Rough and Fuzzy Clustering
SKG '07 Proceedings of the Third International Conference on Semantics, Knowledge and Grid
Terminological concept modelling and conceptual data modelling
International Journal of Metadata, Semantics and Ontologies
An efficient graph-based approach to mining association rules for large databases
International Journal of Intelligent Information and Database Systems
An insight into semantic similarity aspects using WordNet
International Journal of Information and Communication Technology
Word sense disambiguation methods
Programming and Computing Software
Unsupervised learning of verb argument structures
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
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Currently, ontology is widely used in the field of information science, and ontology backbone has been proved to be the major component and a key part of ontology. This paper proposes an acquisition method of ontology backbone, which is expanded on the basis of clustered domain term. Firstly, this method uses Hownet to take segmentation of domain term, and then takes semantic disambiguation for abbreviation based on Hownet and guideless method. Finally, it automatically obtains concept, concept hierarchy and its corresponding instance. Experiment results confirmed that this method is practical and effective.