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Multidimensional Longest Increasing Subsequences and Its Variants Discovery Using DNA Operations

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Mining Intelligence and Knowledge Exploration

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8284))

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Abstract

The Multidimensional Longest Increasing Subsequence (MLIS) and Multidimensional Common Longest Increasing Subsequence (MCLIS) have their importance in many data mining applications. This work finds all increasing subsequences in n sliding window, longest increasing sequences in one and more sequences, decreasing subsequences and common increasing sequences of varied window sizes with one or more dimensions. The proposed work can be applied to finding diverging patterns, constraint MLIS, sequence alignment, find motifs in genetic databases, pattern recognition, mine emerging patterns, and contrast patterns in both, scientific and commercial databases. The algorithms are implemented and tested for accuracy in both real and simulated databases. Finally, the validity of the algorithms are checked and their time complexity are analyzed.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Madras, Chennai, India

    Balaraja Lavanya & Annamalai Murugan

Authors
  1. Balaraja Lavanya
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  2. Annamalai Murugan
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Editor information

Editors and Affiliations

  1. Department of Business Information Systems, FSIC, National University of Ireland, University College Cork, O’Rahilly Buildings, Cork, Ireland

    Rajendra Prasath

  2. Research Centre in Computer Science, V.H.N.Senthikumara Nadar College (Autonomous), 626 001, Virudhunagar, Tamil Nadu, India

    T. Kathirvalavakumar

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Lavanya, B., Murugan, A. (2013). Multidimensional Longest Increasing Subsequences and Its Variants Discovery Using DNA Operations. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_45

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  • DOI: https://doi.org/10.1007/978-3-319-03844-5_45

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03843-8

  • Online ISBN: 978-3-319-03844-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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