透過您的圖書館登入
IP:3.22.51.241
  • 學位論文

Ranking of Trustworthiness of Review opinion on Internet for 3C commodities

Ranking of Trustworthiness of Review opinion on Internet for 3C commodities

指導教授 : 吳帆
若您是本文的作者,可授權文章由華藝線上圖書館中協助推廣。

並列摘要


Since the rapid development of Internet results in fast e-business growth, many large e-malls have been inaugurated (e.g., eBay, Yahoo, Amazon). E-mall attracts a lot of people to shop on the internet since of its convenience. Compared with traditional malls, the e-mall only provides the photos, specification, price, and other screen demonstrations. The consumers can not touch or feel the products before ordering it, as forces consumers to bear the risks before shopping. In the past researches, those study consider usefulness of the reviews, as we knew until now, there is no research focusing on topic-specific search engines for product reviews based on trustworthiness. Thus, this paper proposes the criteria to evaluate the trust degree of reviews, and then builds a search engine to collect the product reviews scattered in opinion websites, the result of search will sort by trust degree. We apply the Spearman’s rank correlation coefficient to evaluate the similarity between our method and experts. Compare with the opinion of experts, the Spearman’s rank correlation coefficient show a high correlation coefficient, it denotes our method is effective to find the trustworthy review on the internet. Thus, the consumers can browse the reviews with ease and reliability through our method.

參考文獻


[3] Benevenuto, F., Magno, G., Rodrigues, T., & Almeida, V. (2010, July). Detecting spammers on twitter, Proceedings of the Seventh Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference CEAS, Washington
[16] Ward, A., & Smith, J. (2003). Trust and mistrust: radical risk strategies in business relationships, Wiley.
[1] Amin, G. R., & Emrouznejad, A. (2011). Optimizing search engines results using linear programming. Expert Systems with Applications, 38(9), 11534-11537.
[2] Bar-Ilan, J., Mat-Hassan, M., & Levene, M. (2006). Methods for comparing rankings of search engine results. Computer Networks, 50(10), 1448–1463
[4] Hsiao, W.F., Chang, T.M. (2008). An incremental cluster-based approach to spam filtering. Expert Systems with Applications, 34, 1599-1608.