발간년도 : [2021]
| 논문정보 |
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| 논문명(한글) |
[Vol.16, No.1] Applying Opinion Mining Techniques for an Analysis of Online Product Reviews |
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| 논문투고자 |
Young-Taek Jin |
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| 논문내용 |
Understanding product characteristics and opinions from product reviews provided in news, reviews, and discussions on the web site help individuals make decisions about purchasing products. Companies need to improve product quality and design efficient marketing strategies. For this, opinion mining is required to find and analyze people's opinions from unstructured text reviews. Opinion mining aims to find people's opinions and feelings about certain products and services. It includes a variety of methods and techniques ranging from finding simple opinions on products or services to comparative opinions for products. In particular, comparative opinions provide practical information compared to simple opinions and emotions because people with experiences related to the product or service to be compared mainly provide specific information on the strengths, weaknesses, and differences of the product or service. However, it is not easy to classify comparison opinions from user reviews, and there are many techniques for this. In this study, we present the comparative results of applying various machine learning techniques to specific product reviews for comparative opinion mining. Through this, it is intended to help understand various techniques for classifying comparative opinions and extracting useful information such as the preference of product attributes. |
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