Abstract
With the advancement in the Internet technology, customers can easily share opinions on services and products in forms of reviews. There can be large amounts 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 language. Thai words are written continuously without space, there is no symbol to signify the end of a sentence, and many reviews are written informally, thus accurate word identification and linguistic annotation cannot be relied upon. This research proposes a novel technique to generate abstractive summaries of customer reviews written in Thai language. The proposed technique, which consists of the local and the global models, is evaluated using actual reviews of fifty randomly selected products from a popular cosmetic website. The results show that the local model outperforms the other model and the two baseline methods both quantitatively and qualitatively.
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