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WRSP-Miner Algorithm for Mining Weighted Sequential Patterns from Spatio-temporal Databases

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Proceedings of the Second International Conference on Computer and Communication Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 379))

Abstract

Not allowing priorities in the mining process does not support user-directed or focus-driven mining. The work proposed in this paper provides support to include user prioritizations in the form of weights into the mining process. An algorithm WRSP-Miner is proposed for the purpose of mining Weighted Regional Sequential Patterns (WRSPs) from spatio-temporal event databases. WRSP-Miner uses two interestingness measures sequence weight and significance index for efficient mining of WRSPs. Experimentation has been performed on synthetic datasets and results proved that the proposed WRSP-Miner algorithm has achieved the purpose of its design.

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Authors and Affiliations

  1. Department of CSE, S. V. University College of Engineering, S. V. University, Tirupati, Andhra Pradesh, India

    Gurram Sunitha & A. Rama Mohan Reddy

Authors
  1. Gurram Sunitha
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  2. A. Rama Mohan Reddy
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Corresponding author

Correspondence to Gurram Sunitha .

Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Department of CSE, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Sunitha, G., Rama Mohan Reddy, A. (2016). WRSP-Miner Algorithm for Mining Weighted Sequential Patterns from Spatio-temporal Databases. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 379. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2517-1_31

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  • DOI: https://doi.org/10.1007/978-81-322-2517-1_31

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2516-4

  • Online ISBN: 978-81-322-2517-1

  • eBook Packages: EngineeringEngineering (R0)

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