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A Context-Aware Recommender System for M-Commerce Applications

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Active Media Technology (AMT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6890))

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Abstract

M-commerce is an attractive research area due to its relative novelty, rapid growth, and great potential in business applications. However, the development of M-commerce applications is facing with some physical constraints of mobile devices and barriers of existing execution models. Moreover, the nomadic users might consume enormous time to search for satisfactory products or services from abundant options with the limited capability of physical devices. Therefore, a sophisticated recommendation algorithm which attempts to recommend a list of user-preferred products or services should be incorporated in M-commerce applications. In this paper, we propose a personalized Context-aware M-commerce Recommender System which exploits the advantages of collaborative filtering and common understanding of contextual information. Since the recommendation algorithm is embedded in a layered system and closed related with other system components, we will present a comprehensive framework to integrate the concepts of mobile agent, ontology-based context model as well as service discovery and selection mechanism. We have developed a prototype to evaluate the feasibility and effectiveness of our proposal.

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Author information

Authors and Affiliations

  1. School of Mathematic and Statistics, Lan zhou University, Lan zhou, Gansu, P.R. China

    Jiazao Lin, Wenqiang Guo & Lian Li

  2. School of Information Science and Engineering, Lan zhou University, Lan zhou, Gansu, P.R. China

    Jiazao Lin, Yi Yang, Li Liu & Lian Li

  3. School of Computer Science, University of Guelph, Guelph, Ontario, Canada

    Xining Li & Xin Li

Authors
  1. Jiazao Lin
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  2. Xining Li
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  3. Yi Yang
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  4. Li Liu
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  5. Wenqiang Guo
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  6. Xin Li
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  7. Lian Li
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Editor information

Editors and Affiliations

  1. Department of Life Science and Informatics, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi-City, 371.0816, Japan

    Ning Zhong

  2. Department of Computer Science, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, Essex, UK

    Vic Callaghan

  3. Faculty of Computer Science, University of New Brunswick, E3B 5A3, Fredericton, N.B., Canada

    Ali A. Ghorbani

  4. School of Information Science and Engineering, Lanzhou University, Feiyun Lou Building, Tianshui South Road 222, 730000, Lanzhou, Gansu, China

    Bin Hu

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© 2011 Springer-Verlag Berlin Heidelberg

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Lin, J. et al. (2011). A Context-Aware Recommender System for M-Commerce Applications. In: Zhong, N., Callaghan, V., Ghorbani, A.A., Hu, B. (eds) Active Media Technology. AMT 2011. Lecture Notes in Computer Science, vol 6890. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23620-4_25

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  • DOI: https://doi.org/10.1007/978-3-642-23620-4_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23619-8

  • Online ISBN: 978-3-642-23620-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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