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:: Volume 33, Issue 3 (Spring 2018) ::
2018, 33(3): 1177-1194 Back to browse issues page
Introducing a machine-based approach for Word Sense Disambiguation: using Lesk algorithm and Part Of Speech tagging
Elham Alayiaboozar
Assistant Professor Iranian Research Institute for Information Science and Technology(IranDoc)
Abstract:   (1561 Views)
Present study introduces a machine-based approach for Word Sense Disambiguation (WSD). In Persian, a morphologically complex language, lots of homographs are made; one way for doing WSD is allocating the right Part Of Speech (POS) tags to words, prior to WSD. Since the frequency of noun and adjective homographs in different Persian text corpuses is high, POS disambiguation of such homographs seems to be necessary for WSD. This paper introduces an approach in which first POS tagging is done, then the output, which is tagged sentences, enters the next step which is POS disambiguation of Persian nouns and adjective homographs; then the output of this step enters the final step which is applying the Lesk algorithm(a kind of unsupervised learning) for WSD. The proposed approach speeds up the WSD procedure by filtering the only relevant glosses (exist in dictionary) and increases the accuracy of the WSD procedure as well.
Keywords: homographs, Word Sense Disambiguation, Part Of Speech tagging, disambiguation of Persian nouns and adjective homographs, Lesk algorithm
Full-Text [PDF 738 kb]   (631 Downloads)    
Type of Study: Research | Subject: Information Technology
Received: 2016/12/4 | Accepted: 2017/05/1 | Published: 2017/06/25
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Alayiaboozar E. Introducing a machine-based approach for Word Sense Disambiguation: using Lesk algorithm and Part Of Speech tagging. Journal of Information Processing and Management. 2018; 33 (3) :1177-1194
URL: http://jipm.irandoc.ac.ir/article-1-3436-en.html


Volume 33, Issue 3 (Spring 2018) Back to browse issues page
پژوهشنامه پردازش و مدیریت اطلاعات Journal of Information processing and Management
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