DOI: 10.18178/wcse.2019.03.019
Trust Recommendation System in Online Shopping Using Text Mining
Abstract— In online society, understanding the methods of trust is essential. In addition, issues of trust are necessary to several solving problems corporate responsibility, online shopping, and the social system. Trust is a concept with many facets and dimensions. Many trust evaluations have been proposed, which used direct ratings from user to calculation or propagat ion of trust values. In some web -based social networks technology that is no direct rat ing value where users are calculated by binary relationships. The benefit of this paper is to examine the importance of trust in online shopping, which trust value is calculated by without any direct ratings from consumers. In this calculat ion, which is based calculate on opinion, user similarity is based from the texts comments by the users for the trust with text -mining techniques using Sentiment Analysis and then evaluate with Improved PageRank. Moreover, this system approach in web-based social networks and proposed technique can also be help in direct rating methods to calculate the correct values of trust in online services.
Index Terms— Online Shopping, Sentiment Analysis, Improved PageRank Algorithm, Text Mining.
Hla Sann Sint, Khine Khine Oo
University of Computer Studies, MYANMAR
Cite: Hla Sann Sint, Khine Khine Oo, "Trust Recommendation System in Online Shopping Using Text Mining," Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering WCSE_2019_SPRING, pp. 107-111, Yangon, Myanmar, February 27-March 1, 2019.