Acquiring lexical knowledge using raw corpora and unsupervised clustering method

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4

초록

In this paper, we propose a computational model for automatic acquisition of lexical knowledge based on the principles of human language information processing. The proposed model assumes a hybrid model for the human lexical representation including full-list and decomposition forms. The proposed method automatically acquires lexical entries and its grammatical knowledge by unsupervised learning techniques. For the purposes of evaluating performance of the proposed method, a large-scale corpus of over 10 million lexical was used, the lexical knowledge acquisition process was tested, and the results were analyzed.

키워드

Lexical knowledge acquisition; Mental lexicon; SOM; Entropy; VISUAL WORD RECOGNITION; INTERNAL LEXICON; AFFIXED WORDS; REPRESENTATION; MORPHOLOGY; MODEL; FREQUENCY
제목
Acquiring lexical knowledge using raw corpora and unsupervised clustering method
저자
Park, Kinam; Lim, Heuiseok
DOI
10.1007/s10586-013-0306-3
발행일
2014-09
유형
Article
저널명
Cluster Computing
권
17
호
3
페이지
901 ~ 910