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

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

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International World Wide Web Conference archive
Proceedings of the 16th international conference on World Wide Web table of contents

Banff, Alberta, Canada

POSTER SESSION: Services table of contents

Pages: 1251 - 1252

Year of Publication: 2007

ISBN:978-1-59593-654-7

Authors

Qiudan Li	Chinese Academy of Sciences, Beijing, China
Chunheng Wang	Chinese Academy of Sciences, Beijing, China
Guanggang Geng	Chinese Academy of Sciences, Beijing, China
Ruwei Dai	Chinese Academy of Sciences, Beijing, China

Sponsor

ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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ABSTRACT

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 m-commerce. This paper proposes a novel collaborative filtering-based 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 m-commerce. We implemented it in an existing m-commerce platform, and experimental results demonstrate its feasibility and correctness.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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