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A Method for Mobility Management in Cellular Networks Using Data Mining

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Context-Aware Systems and Applications (ICCASA 2016)

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Abstract

The Mobility prediction is one of the important issues in mobile computing systems. The moving logs of mobile users in mobile computing environment are stored in the Home Location Registry (HLR). The generated moving logs are used for mining mobility patterns. The discovered location patterns can be used to provide various location based services to the mobile user by the application server in mobile computing environment. Currently, some papers have written about mobility data mining methods of mobile users in cellular communications networks. In this paper, we propose a method which decrease time to compute the mobility patterns.

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Notes

  1. 1.

    B. Sanou. (2015, May) www.itu.int/ict. [Online]. https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2015.pdf.

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Author information

Authors and Affiliations

  1. HCM City University of Technology, Ho Chi Minh City, Vietnam

    Giang Minh Duc & Do Hong Tuan

  2. Van Hien University, Ho Chi Minh City, Vietnam

    Le Manh

Authors
  1. Giang Minh Duc
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  2. Le Manh
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  3. Do Hong Tuan
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Corresponding author

Correspondence to Giang Minh Duc .

Editor information

Editors and Affiliations

  1. Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Phan Cong Vinh

  2. Thu Dau Mot University, Thu Dau Mot City, Vietnam

    Le Tuan Anh

  3. Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Nguyen Thi Thuy Loan

  4. University of the Thai Chamber of Commerce, Bangkok, Thailand

    Waralak Vongdoiwang Siricharoen

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Duc, G.M., Manh, L., Tuan, D.H. (2017). A Method for Mobility Management in Cellular Networks Using Data Mining. In: Cong Vinh, P., Tuan Anh, L., Loan, N., Vongdoiwang Siricharoen, W. (eds) Context-Aware Systems and Applications. ICCASA 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-319-56357-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-56357-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56356-5

  • Online ISBN: 978-3-319-56357-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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