EuroWordNet: a multilingual database with lexical semantic networks
EuroWordNet: a multilingual database with lexical semantic networks
Corelex: systematic polysemy and underspecification
Corelex: systematic polysemy and underspecification
Natural Language Engineering
Reducing lexical semantic complexity with systematic polysemous classes and underspecification
NLPComplexity '00 NAACL-ANLP 2000 Workshop: Syntactic and Semantic Complexity in Natural Language Processing Systems
Extraction of Word Senses from Human Factors in Knowledge Discovery
DS '02 Proceedings of the 5th International Conference on Discovery Science
Methodology and construction of the Basque WordNet
Language Resources and Evaluation
Establishment of taxonomic relationships in linguistic ontologies
KONT'07/KPP'07 Proceedings of the First international conference on Knowledge processing and data analysis
A concept identification method for Vietnamese concept-based information retrieval system
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
| Hi-index | 0.00 |
We examine three different types of sense clustering criteria with an Information Retrieval application in mind: methods based on the wordnet structure (such as generalization, cousins, sisters…); co-occurrence of senses obtained from Semcor; and equivalent translations of senses in other languages via the EuroWordNet InterLingual Index (ILI). We conclude that a) different NLP applications demand not only different sense granularities but different (possibly overlapped) sense clusterings. b) co-occurrence of senses in Semcor provide strong evidence for Information Retrieval clusters, unlike methods based on wordnet structure and systematic polysemy, c) parallel polysemy in three or more languages via the ILI, besides providing sense clusters for MT and CLIR, is strongly correlated with co-occurring senses in Semcor, and thus can be useful for Information Retrieval as well.