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An Approach to Optimize Fuzzy Time-Interval Sequential Patterns Using Multi-objective Genetic Algorithm

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Technology Systems and Management

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 145))

Abstract

Sequential pattern mining, which discovers frequent subsequences as patterns in a sequence database, is an important data-mining problem with broad applications. From these discovered sequential patterns, we can discover the order of the patterns; however, they cannot tell us the time intervals between successive patterns. Accordingly, Chen et al. have proposed a fuzzy time-interval (FTI) sequential pattern mining algorithms, which reveals the time intervals between successive patterns [12][13]. In this paper, we contributed to the ongoing research on FTI sequential pattern mining by proposing a multi objective Genetic Algorithm (GA) based method. Fuzzy solves the sharp boundary problem and the refinement ability of GA helps to find the global optimum FTI sequential patterns. Our approach uses two measures as objectives, namely: Confidence and Coverage to prune the traditional Apriori algorithm. The main objective is to achieve maximum confidence and maximum coverage in the FTI sequential patterns. The paper defines the confidence of the FTI sequences, which is not yet defined in the previous researches. The main advantage of the proposed algorithm is the use of fuzzy genetic approach to discover optimized sequences in the network traffic data to classify and detect intrusion.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, M.E.T, Bandra, Mumbai, India

    Sunita Mahajan

  2. Computer Department, MPSTME, SVKM’s NMIMS University, Mumbai, India

    Alpa Reshamwala

Authors
  1. Sunita Mahajan
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  2. Alpa Reshamwala
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Editor information

Editors and Affiliations

  1. SVKM’s NMIMS, MPSTME, Mukesh Patel School of Technology Management and Engineering, Bhakti Vedant Swami Marg, JVPD, 400056, Vile- Parle (W) Mumbai, Maharashtra, India

    Ketan Shah

  2. SVKM’s NMIMS, MPSTME Mukesh Patel School of Technology Management and Engineering, Bhakti Vedant Swami Marg, JVPD, 400056, Vile- Parle (W), Mumbai, Maharashtra, India

    V. R. Lakshmi Gorty

  3. SVKM’s NMIMS, MPSTME, Mukesh Patel School of Technology Management and Engineering, Bhakti Vedant Swami Marg, JVPD, 400056, Vile- Parle (W), Mumbai, Maharashtra, India

    Ajay Phirke

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© 2011 Springer-Verlag Berlin Heidelberg

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Mahajan, S., Reshamwala, A. (2011). An Approach to Optimize Fuzzy Time-Interval Sequential Patterns Using Multi-objective Genetic Algorithm. In: Shah, K., Lakshmi Gorty, V.R., Phirke, A. (eds) Technology Systems and Management. Communications in Computer and Information Science, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20209-4_16

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  • DOI: https://doi.org/10.1007/978-3-642-20209-4_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20208-7

  • Online ISBN: 978-3-642-20209-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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