Processing dictionary definitions with phrasal pattern hierarchies
Computational Linguistics - Special issue of the lexicon
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
EuroWordNet: a multilingual database with lexical semantic networks
EuroWordNet: a multilingual database with lexical semantic networks
Modern Information Retrieval
An evaluation of term dependence models in information retrieval
SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval
Automatic Generation of Hierarchical Taxonomies from Free Text Using Linguistic Algorithms
OOIS '02 Proceedings of the Workshops on Advances in Object-Oriented Information Systems
MindNet: acquiring and structuring semantic information from text
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Semantically significant patterns in dictionary definitions
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
Extracting semantic hierarchies from a large on-line dictionary
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Reformulation of queries using similarity thesauri
Information Processing and Management: an International Journal
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This paper proposes a pattern matching method applied to dictionaries to identify hierarchical relationships between terms. In this work we focus on this type of relationship because we use it in the automatic generation of thesauri, which are used to improve information retrieval tasks. However the method can also be applied to identify other semantic relationships. We distinguish two kinds of patterns: structural patterns, composed of a sequence of part-of-speech tags, and key patterns, typical of dictionary entries, composed of some key terms, along with some part-of-speech tags. This kind of patterns are automatically extracted for the dictionary entries by means of stochastic techniques. The thesaurus, that has been partially constructed previously, is then extended with the new relationships obtained by applying the patterns to a dictionary. We have based the system evaluation on the results obtained with and without the thesaurus in an information retrieval task proposed by the Cross-Language Evaluation Forum (CLEF). The results of these experiments have revealed a clear improvement on the performance.