IEEE Transactions on Pattern Analysis and Machine Intelligence
The ATRACT Workbench: Automatic Term Recognition and Clustering for Terms
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Identifying terms by their family and friends
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Term Clustering Using a Corpus-Based Similarity Measure
TSD '02 Proceedings of the 5th International Conference on Text, Speech and Dialogue
Terminology-driven mining of biomedical literature
Proceedings of the 2003 ACM symposium on Applied computing
Using automatically learnt verb selectional preferences for classification of biomedical terms
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
An integrated term-based corpus query system
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Automatic discovery of term similarities using pattern mining
COMPUTERM '02 COLING-02 on COMPUTERM 2002: second international workshop on computational terminology - Volume 14
Mining semantically related terms from biomedical literature
ACM Transactions on Asian Language Information Processing (TALIP)
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In this paper we present a method for the automatic discovery and tuning of term similarities. The method is based on the automatic extraction of significant patterns in which terms tend to appear. Beside that, we use lexical and functional similarities between terms to define a hybrid similarity measure as a linear combination of the three similarities. We then present a genetic algorithm approach to supervised learning of parameters that are used in this linear combination. We used a domain specific ontology to evaluate the generated similarity measures and set the direction of their convergence. The approach has been tested and evaluated in the domain of molecular biology.