Title :
E-Commerce Reviews Management System Based on Online Customer Reviews Mining
Author :
Bin, Deng ; Peiji, Shao ; Dan, Zhao
Author_Institution :
Sch. of Mgmt & Econ., Univ. of Elec. Sci. & Tech. of China, Chengdu, China
Abstract :
E-commerce website accumulates a large number of customer reviews for merchandise and online shopping services. E-commerce enterprises and manufacturers could get customer opinion to improve service and merchandise through mining customer reviews. The paper presents a prototype system could be used to track and manage customer reviews, through mining topics and sentiment orientation from online customer reviews. The paper studied Chinese reviews mining processing steps and methods. Finally, this study applied text mining to costumer reviews. Through case study, the method can efficiently identify topics to enterprises.
Keywords :
Web sites; data mining; electronic commerce; home shopping; e-commerce Web site; e-commerce reviews management system; merchandise services; online customer reviews mining; online shopping services; text mining; Conference management; Data mining; Information technology; Innovation management; Manufacturing; Merchandise; Mouth; Oceans; Text mining; Underwater communication; E-commerce; online customer reviews; opinion mining; text mining;
Conference_Titel :
Innovative Computing & Communication, 2010 Intl Conf on and Information Technology & Ocean Engineering, 2010 Asia-Pacific Conf on (CICC-ITOE)
Conference_Location :
Macao
Print_ISBN :
978-1-4244-5634-5
Electronic_ISBN :
978-1-4244-5635-2
DOI :
10.1109/CICC-ITOE.2010.100
