A semantic-expansion approach to personalized knowledge recommendation

The rapid propagation of the Internet and information technologies has changed the nature of many industries. Fast response and personalized recommendations have become natural trends for all businesses. This is particularly important for content-related products and services, such as consulting, news, and knowledge management in an organization. The digital nature of their products allows for more customized delivery over the Internet. To provide personalized services, however, a complete understanding of user profile and accurate recommendation are essential. In this paper, an Internet recommendation system that allows customized content to be suggested based on the user's browsing profile is developed. The method adopts a semantic-expansion approach to build the user profile by analyzing documents previously read by the person. Once the customer profile is constructed, personalized contents can be provided by the system. An empirical study using master theses in the National C...

• Type: Journal
• Year: 2008
• Where: DSS
• Authors: Ting-Peng Liang, Yung-Fang Yang, Deng-Neng Chen, Yi-Cheng Ku
• Keywords: DSS 2008, Personalized, Semantic-expansion Approach, User Profile