Extracting Emotional Units based on POS Templates

doi:10.23940/ijpe.18.02.p17.357362

Abstract

Abstract:

With the increasingly popularity of electronic commerce, a large number of product reviews appeared in electronic commerce websites, which implicated a lot of valuable business information. Sentiment analysis is the core issue in disposing of business information, and the product feature words and sentiment words extraction are key technology that affect the quality of sentiment analysis. This paper proposes a simultaneous extraction algorithm of product feature words and sentiment words based on part-of-speech(POS) relation templates. Firstly, we extract possible POS dependency templates in a training set by using the supervised sequence rules mining algorithm. Secondly, we use the templates in the test samples to extract possible two tuple of product feature words and sentiment words. Finally, we test this method in a hotel review corpus. The experimental results show that this proposed method has a good application effect.

Zhenggao Pan and Lili Chen. Extracting Emotional Units based on POS Templates [J]. Int J Performability Eng, 2018, 14(2): 357-362.

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