C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Building accurate semantic taxonomies from monolingual MRDs
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Extracting semantic hierarchies from a large on-line dictionary
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Distributional clustering of English words
ACL '93 Proceedings of the 31st 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
Automatic construction of a hypernym-labeled noun hierarchy from text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
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Most approaches for extracting hypernyms of a noun from the definition in an MRD rely on the lexico-syntactic patterns compiled by human experts. Not only these methods require high cost for compiling lexico-syntatic patterns but also it is very difficult for human experts to compile a set of lexical-syntactic patterns with a broad-coverage, because in natural languages there are various different expressions which represent the same concept. To alleviate these problems, this paper proposes a new method for extracting hypernyms of a noun from an MRD. In proposed approach, we use only syntactic(part-of-speech) patterns instead of lexico-syntactic patterns in identifying hypernyms to reduce the number of patterns while keeping their coverage broad. Our experiment shows that the classification accuracy of the proposed method is 92.37% which is significantly much better than those of previous approaches.