Aide à la conception de méthodes de classification pour la construction d'ontologies : l'atelier Mo'K.
作者： Claire Nedellec , Gilles Bisson
DOI:
关键词:
摘要: This paper describes Mo’K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo’K is intended to assist developers in exploratory process defining most suitable learning given task. To do so, it provides facilities evaluation, comparison and elaboration methods. Also, model underlying permits fine-grained definition similarity measures class construction operators, easing tasks method instantiation configuration. presents some experimental results illustrate suitability help characterize assess performance different learn semantic classes from parsed corpora
参考文章(35)
Gilles Bisson, Conceptual clustering in a first order logic representation european conference on artificial intelligence. pp. 458- 462 ,(1992)
Philip Resnik, Marti A. Hearst, Structural Ambiguity and Conceptual Relations meeting of the association for computational linguistics. ,(1993)
Wide R. Hogenhout, Yuji Matsumoto, A Preliminary Study of Word Clustering Based on Syntactic Behavior conference on computational natural language learning. pp. 16- 24 ,(1997)
Fernando Gomez, Linking WordNet Verb Classes to Semantic Interpretation. international conference on computational linguistics. ,(1998)
Francesc Ribas, An Experiment on Learning Appropriate Selectional Restrictions from a Parsed Corpus arXiv: Computation and Language. ,(1994)
Ryszard S. Michalski, Robert E. Stepp, Learning from Observation: Conceptual Clustering Machine Learning. pp. 331- 363 ,(1983) , 10.1007/978-3-662-12405-5_11
Benit Habert, Les linguistiques de corpus Armand Colin. pp. 240- ,(1997)
João José Furtado Vasco, Colette Faucher, Eugène Chouraqui, A Knowledge Acquisition Tool for Multi-Perspective Concept Formation knowledge acquisition, modeling and management. pp. 229- 244 ,(1996) , 10.1007/3-540-61273-4_15
Luis Talavera, Javier Béjar, Efficient construction of comprehensible hierarchical clusterings Principles of Data Mining and Knowledge Discovery. pp. 93- 101 ,(1998) , 10.1007/BFB0094809
Patrick Hanks, Kenneth Ward Church, Word association norms, mutual information, and lexicography Computational Linguistics. ,vol. 16, pp. 22- 29 ,(1990) , 10.5555/89086.89095