Title :
An opinion search system for consumer products
Author :
Miao, Qingliang ; Li, Qiudan
Author_Institution :
Key Lab. of Complex Syst. & Intell. Sci., Chinese Acad. of Sci., Beijing
Abstract :
With the rapid progress of e-commerce, many people like purchasing product on the e-commerce Website, and giving their personal reviews to the product they purchased, so the number of customer reviews grows rapidly. Generally, a potential customer will browse product reviews before they purchase the product. However, retrieving opinions relevant to customerpsilas desire still remains challenging. To provide efficient opinion information for customers, we propose an opinion search system for consumer products, which utilizes data mining and information retrieval technology. A ranking mechanism taking temporal dimension into account and a method for results visualization are developed in the system. Experimental results on a real-world data set show the system is feasible and effective.
Keywords :
Web sites; consumer products; data mining; electronic commerce; information retrieval; purchasing; Website; consumer product; data mining; e-commerce; information retrieval technology; opinion search system; purchasing product; real-world data set; Consumer products; Neural networks;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4633985