Title :
Web product ranking using opinion mining
Author :
Yin-Fu Huang ; Heng Lin
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Yunlin Univ. of Sci. & Technol., Yunlin, Taiwan
Abstract :
Online shopping is becoming increasingly important as more and more manufacturers sell products on the Internet, and many users are using the Internet to express and share their opinions. However, it is impossible for consumers to read all product reviews. Therefore, it is necessary to design effective systems to summarize the pros and cons of product characteristics, so that consumers can quickly find their favorable products. In this paper, we present a product ranking system using opinion mining techniques. Users can specify product features to get back the ranking results of all matched products. In this system, we consider three issues while calculating product scores: 1) product reviews, 2) product popularity, and 3) product release month. Finally, the experimental results show that the system is practical and the ranking results are interesting.
Keywords :
Internet; data mining; information retrieval; pattern classification; retail data processing; Internet; Web product ranking system; online shopping; opinion mining techniques; product popularity; product ranking system; product release month; product reviews; product score; Data mining; HTML; Internet; Tagging; User interfaces; XML; POS; XML document; information retrieval; opinion mining;
Conference_Titel :
Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on
Conference_Location :
Singapore
DOI :
10.1109/CIDM.2013.6597235