Word sense disambiguation of opinionated words using extended gloss overlap
Date of Publication
2011
Document Type
Master's Thesis
Degree Name
Master of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Charibeth K. Cheng
Abstract/Summary
The increasing use of digital technology and social media has prompted government organizations to take advantage of these in order to gather feedback and opinions from the general public on policies and laws. Since people’s opinions vary, there is a need to present these in an orderly manner for faster and more efficient decision and policy making. This is where opinion classification comes in. Existing systems such as Vox Pop are able to classify texts according to polarity with the help of SentiWordNet, which assigns subjectivity and polarity scores to WordNet synsets. However, the current algorithm that Vox Pop uses yields an accuracy rate of only 50.5%. The research integrated a word sense disambiguation algorithm may be the key to improving the task of polarity classification. The extended gloss overlap algorithm was be used, which compares two synsets and scores the relatedness between them by looking for phrasal matches between all their glosses. However, the accuracy only increased to 60%. This shows that integrating WSD is not enough in improving the opinion classification task.
Abstract Format
html
Language
English
Format
Accession Number
TG04995; CDTG004995
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
vi, 65 leaves ; 28 cm. + 1 computer optical disc.
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Recommended Citation
Razon, B. C. (2011). Word sense disambiguation of opinionated words using extended gloss overlap. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/4009