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Ohm Sornil
Graduate School of Applied Statistics, National Institute of Development Administration, 118 Seri-Thai Road, Bangkapi, Bangkok, 10240,
Computer Science & IT

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Using Cultural and Social Beliefs in Language Games Theerapol Limsatta; Ohm Sornil
Journal of ICT Research and Applications Vol. 10 No. 3 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.3.5

Abstract

Agreement on word-object pairing in communication depends on the intensity of the beliefs that gradually emerge in a society of agents, on the condition that no one was born with embedded knowledge. The agents search and exchange ideas about unknown word-object pairings, until they meet a consensus about what the object should be named. A language game is a social process of finding agreement on word-object pairings through communication in a multi-agent system. In this paper, a technique is proposed to discover the association between a word and the agents' beliefs on an object using self-organizing maps and a cultural algorithm in a multi-hearer environment. A conceptual space is implemented, which stores the agent's beliefs in three dimensions, represented by colors. The technique was evaluated for a variety of scenarios using four significant measures: coherence, specificity, success rate, and word size. The results showed that with the proposed method social agents can reach agreement fast and that their communication is effective.
A Hierarchical Emotion Classification Technique for Thai Reviews Jirawan Charoensuk; Ohm Sornil
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.6

Abstract

Emotion classification is an interesting problem in affective computing that can be applied in various tasks, such as speech synthesis, image processing and text processing. With the increasing amount of textual data on the Internet, especially reviews of customers that express opinions and emotions about products. These reviews are important feedback for companies. Emotion classification aims to identify an emotion label for each review. This research investigated three approaches for emotion classification of opinions in the Thai language, written in unstructured format, free form or informal style. Different sets of features were studied in detail and analyzed. The experimental results showed that a hierarchical approach, where the subjectivity of the review is determined first, then the polarity of opinion is identified and finally the emotional label is calculated, yielded the highest performance, with precision, recall and F-measure at 0.691, 0.743 and 0.709, respectively.
Co-Authors Jirawan Charoensuk Theerapol Limsatta