To Adapt to Changes in the User Long-Term and Recent Interest of Personalized Recommendation Model

Abstract:

With the development and popularization of the information superhighway, people are surrounded by the sea of information. Exponential expansion of Internet information resources, is the vast amounts of information source, its information organization is heterogeneous, diverse, distribution and other features. therefore, can provide users with effective information recommendation, help users to find the valuable information you need the personalized recommendation system won wide attention in the field of Web information retrieval, and also in actual personalization service system has been widely applied in this paper, the personalized services recommendation system architecture to do some research, proposed a distinguishing the user long-term interests and immediate interests provide information to recommend a new model of personalized recommendation.

• Periodical: Advanced Materials Research (Volumes 791-793)
• Pages: 2143-2146
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.791-793.2143
• Online since: September 2013
• Authors: Hua Yue Chen, Jing Pu
• Keywords: Current Interest View, Long-Term Interest, Personalized Recommendation, Recent Interest, Weighted Association Rules

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