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http://dx.doi.org/10.9716/KITS.2018.17.2.165

Analysis of the Online Review Based on the Theme Using the Hierarchical Attention Network  

Jang, In Ho (연세대학교 정보대학원)
Park, Ki Yeon (연세대학교 정보대학원)
Lee, Zoon Ky (연세대학교 정보대학원)
Publication Information
Journal of Information Technology Services / v.17, no.2, 2018 , pp. 165-177 More about this Journal
Abstract
Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.
Keywords
Deep Learning; Hierarchical Attention Network; Online Market; Online Customer Review; Web Text Analysis;
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