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James R. Curran and Marc Moens.
Improvements in Automatic Thesaurus Extraction.
In Proceedings of the Workshop of the ACL Special Interest Group on the Lexicon (SIGLEX),
pp. 59-66,
2002.
Improvements in Automatic Thesaurus Extraction.
In Proceedings of the Workshop of the ACL Special Interest Group on the Lexicon (SIGLEX),
pp. 59-66,
2002.
Abstract: The use of semantic resources is common in modern NLP systems, but methods to extract lexical semantics have only recently begun to perform well enough for practical use. We evaluate existing and new similarity metrics for thesaurus extraction, and experiment with the tradeoff between extraction performance and efficiency. We propose an approximation algorithm, based on canonical attributes and coarse- and fine-grained matching, that reduces the time complexity and execution time of thesaurus extraction with only a marginal performance penalty.
thesaurus extraction systems -> differ in the definition of "context"
used a statistical shallow parser
frequency cutoff speeds up the calculation, but doesn't decrease the performance
misc. topics: weights, measures, cutoff frequency, speed-up by canonical vectors
canonical vectors: subj+dobj+iobj, TTestLog + maximum frequency cutoff
used a statistical shallow parser
frequency cutoff speeds up the calculation, but doesn't decrease the performance
misc. topics: weights, measures, cutoff frequency, speed-up by canonical vectors
canonical vectors: subj+dobj+iobj, TTestLog + maximum frequency cutoff
updated at: 2007/07/07 17:25:42