Abstractive Thai opinion summarization
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2013
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2556
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eng
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55 leaves
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b184490
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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National Institute of Development Administration. Library and Information Center
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Orawan Chaowalit (2013). Abstractive Thai opinion summarization. Retrieved from: http://repository.nida.ac.th/handle/662723737/3028.
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Abstractive Thai opinion summarization
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Abstract
With the advancement of the Internet technology, customers can easily share
opinions about services and products in forms of reviews. There can be large amount
of reviews for popular products. Manually summarizing those reviews for important
issues is a daunting task. Automatic opinion summarization is a solution to the
problem. The task is more complicated for reviews written in Thai. Thai words are
written continuously without space, and there is no symbol to identify the end of a
sentence. Many reviews are written informally, thus accurate word identification and
linguistic annotation cannot be relied upon. Text summarization can be classified into
two categories, which are extractive and abstractive summarization. In the extractive
method, the summary is a set of actual sentences or phrases extracted from the
reviews; on the other hand, abstractive summarization does not output original
sentences from the reviews, but generates new sentences or phrases into a summary.
The abstractive summarization approach is more difficult and thus less popular than
the extractive approach. This research proposes a novel technique to generate
abstractive summaries of customer reviews written in Thai. The proposed technique,
which consists of local and global models, is evaluated by using actual reviews of
fifty products, randomly selected from a popular cosmetic website. The results show
that the local model outperforms the global model and the two baseline methods, both
quantitatively and qualitatively.
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Dissertation (Ph.D. (Computer Science)) National Institute of Development Administration, 2013.