The Design of a Social Commerce Recommendation System Based on Semantic Web Technology

• Main Authors: Ching-Ping, Tsai, 蔡京玶
• Other Authors: Hsu-Yang, Kung
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/70200337583115301751

碩士 === 國立屏東科技大學 === 資訊管理系所 === 100 === Among the vigorous developments of the network, E-Commerce becomes one of the important channels for marketing and sale today. The development of Social Commerce, such as group buying website, is also the major force to drive the growth on E-commerce in recent years. However, users need to spend much time to search the discount information on different group buying websites. In this paper, we propose the Social Commerce Recommendation System (SCRS) which contains Merchandise Information Collection Layer (MICL), Merchandise Semantic Web Layer (MSWL), Content-based Information Filtering Layer (CIFL), and Merchandise Information Recommendation Layer (MIRL). In the implementation, we obtain the discount information to establish the MICL from the group buying websites such as GrouponTW, Gomaji, 17 Life and so on. The MSWL uses the Merchandise Ontology (MO) and Personal Ontology (PO) based on Semantic Web (SW). The CIFL calculates the matching coefficient and infers suitable discount information for users and shows the result on MIRL. Eventually, users can get the suitable merchandise recommendation and can shorten the time for them to retrieval and filtering the discount information on group buying websites.