Mining Digital Word of Mouth for Product Recommendation

• Main Authors: Chih-WeiWang, 王志瑋
• Other Authors: Shen-Tun Li
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/05119747715859461758

碩士 === 國立成功大學 === 資訊管理研究所 === 100 === With the advent of internet, many users usually search the product specification and reviews as the reference before buying by internet. Unfortunately, there exists a lot of spam information that users cannot find the key information in a short time. Therefore, some researchers have proposed a variety of recommendation methods to solve this problem, such as Feature-based, Collaborative filtering-based, Content-based, Demographic-based, Knowledge-based, Trust-based, etc. However, the most of methods still cannot fulfill the user need of product features quality and reliability simultaneously. So this study proposed trust-based fuzzy TOPSIS method to improve this problem. To reach our target, our method includes of fuzzy MADM, opinion mining, and social trust scores. This study also hopes our proposed method could provide researcher with some idea to extend.