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Acquiring lexical knowledge using raw corpora and unsupervised clustering method

Authors
Park, KinamLim, Heuiseok
Issue Date
9월-2014
Publisher
SPRINGER
Keywords
Lexical knowledge acquisition; Mental lexicon; SOM; Entropy
Citation
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.17, no.3, pp.901 - 910
Indexed
SCIE
SCOPUS
Journal Title
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume
17
Number
3
Start Page
901
End Page
910
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/97531
DOI
10.1007/s10586-013-0306-3
ISSN
1386-7857
Abstract
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.
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