A novel collaborative filtering-based framework for personalized services in m-commerce

With the rapid growth of wireless technologies and handheld devices, m-commerce is becoming a promising research area. Personalization is especially important to the success of mcommerce. This paper proposes a novel collaborative filteringbased framework for personalized services in m-commerce. The framework extends our previous work by using Online Analytical Processing (OLAP) to represent the relations among user, content and context information, and adopting a multi-dimensional collaborative filtering model to perform inference. It provides a powerful and well-founded mechanism to personalization for mcommerce. We implemented it in an existing m-commerce platform, and experimental results demonstrate its feasibility and correctness. Categories and Subject Descriptors H.2.8 [Database Applications]: Data mining; H.3.5 [Online Information Services]: Web-based services. General Terms Algorithms, Experimentation, Human Factors. Keywords Personalization, collaborative filtering, m-commer...

• Type: Conference
• Year: 2007
• Where: WWW
• Authors: Qiudan Li, Chunheng Wang, Guanggang Geng, Ruwei Dai
• Keywords: Collaborative Filtering Model, Collaborative Filteringbased Framework, Internet Technology, M-commerce Platform, WWW 2007