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http://dx.doi.org/10.9723/jksiis.2022.27.1.049

A Study of Customer Review Analysis for Product Development based on Korean Language Processing  

Woo, JeHyuk (한국과학기술원 산업 및 시스템공학과)
Jeong, MinKyu (한국과학기술원 산업 및 시스템공학과)
Lee, JaeHyun (대구대학교 융합산업공학과)
Suh, HyoWon (한국과학기술원 산업 및 시스템공학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.27, no.1, 2022 , pp. 49-62 More about this Journal
Abstract
Online customer review data can be easily collected on the Internet and also they describe sentimental evaluation of a product in different aspects. Previous sentiment analysis studies evaluate the degree of sentiment with review data, which may have multiple sentences describing different product aspects. Since different aspects of a product can be described in a sentence, the proposed method suggested analyzing a sentence to build a pair of a product aspect terms and sentimental terms. Bidirectional LSTM and CRF algorithms were used in this paper. A pair of aspect terms and sentimental terms are evaluated by pre-defined evaluation rules. The paper suggested using the result of evaulation as inputs of QFD, so that the quantified customer voices effect on the requirements of a new product. Online reviews for a hair dryer were used as an example showing that the proposed approach can derive reasonable sentiment analysis results.
Keywords
Sentiment Analysis; LSTM; CRF; QFD;
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