WordNet: a lexical database for English
Communications of the ACM
An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Learning Logic Models for Automated Text Categorization
AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
A General Similarity Framework for Horn Clause Logic
Fundamenta Informaticae
Version spaces: a candidate elimination approach to rule learning
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 1
Plugging Taxonomic Similarity in First-Order Logic Horn Clauses Comparison
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Revising the wordnet domains hierarchy: semantics, coverage and balancing
MLR '04 Proceedings of the Workshop on Multilingual Linguistic Ressources
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Automatic processing of text documents requires techniques that can go beyond the lexical level, and are able to handle the semantics underlying natural language sentences. A support for such techniques can be provided by taxonomies that connect terms to the underlying concepts, and concepts to each other according to different kinds of relationships. An outstanding example of such a kind of resources is WordNet. On the other hand, whenever automatic inferences are to be made on a given domain, a generalization technique, and corresponding operational procedures, are needed. This paper proposes a generalization technique for taxonomic information and applies it to WordNet, providing examples that prove its behavior to be sensible and effective.