Fuzzy Set Theoretic Approach To Collocation Extraction
Author(s) -
Raj Kishor Bisht,
H.S. Dhami
Publication year - 2010
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/895-1269
Subject(s) - computer science , collocation (remote sensing) , extraction (chemistry) , set (abstract data type) , fuzzy logic , artificial intelligence , data mining , machine learning , chromatography , programming language , chemistry
Fuzzy approach deals with the linguistic properties of elements such as beauty, coldness, hotness etc. Collocations are linguistically motivated. Decision of word combination for being collocation is a linguistic term as merely co occurrence of word combinations does not signify the presence of collocation. Thus collocation extraction can be made possible by looking its linguistic aspect. In the present paper, an attempt has been made to make two different fuzzy sets of word combinations to be considered for collocations. Mutual information and t-test have been taken as basis for the construction of fuzzy sets. Two fuzzy set theoretical models have been proposed to identify collocations. It has been shown that fuzzy set theoretical approach works very well for collocation extraction. The working data has been based on a corpus of about one million words contained in different novels constituting project Gutenberg available on www.gutenberg.org.
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