Volume 33, Issue 3 (Spring 2018)                   ... 2018, 33(3): 1165-1182 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Alayiaboozar E. Introducing a Machine-Based Approach for Word Sense Disambiguation: Using Lesk Algorithm and Part of Speech Tagging. .... 2018; 33 (3) :1165-1182
URL: http://jipm.irandoc.ac.ir/article-1-3436-en.html
Iranian Research Institute for Information Science and Technology(IranDoc)
Abstract:   (2021 Views)
The present study introduces a machine-based approach for word sense disambiguation (WSD). In Persian, a morphologically complex language, POS tag which 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 POS tag text corpuses is high, POS tag 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 (existing in dictionary) and increases the accuracy of the WSD procedure as well.
Full-Text [PDF 771 kb]   (782 Downloads)    
Type of Study: Research | Subject: Information Technology
Received: 2016/12/4 | Accepted: 2017/05/1 | Published: 2017/06/25

Add your comments about this article : Your username or Email:

Send email to the article author

© 2019 All Rights Reserved | Iranian Journal of Information processing and Management

Designed & Developed by : Yektaweb