A study on sequential pattern mining on chemical information

  • Authors

    • S Sathya
    • N Rajendran
    https://doi.org/10.14419/ijet.v7i2.33.14828

    Received date: June 30, 2018

    Accepted date: June 30, 2018

    Published date: June 8, 2018

  • Data Mining (DM), Chemical Compounds, Chemical Bonding, Sequential Pattern Mining

  • Abstract

    Data mining (DM) is used for extracting the useful and non-trivial information from the large amount of data to collect in many and diverse fields. Data mining determines explanation through clustering visualization, association and sequential analysis. Chemical compounds are well-defined structures compressed by a graph representation. Chemical bonding is the association of atoms into molecules, ions, crystals and other stable species which frame the common substances in chemical information. However, large-scale sequential data is a fundamental problem like higher classification time and bonding time in data mining with many applications. In this work, chemical structured index bonding is used for sequential pattern mining. Our research work helps to evaluate the structural patterns of chemical bonding in chemical information data sets.

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  • How to Cite

    Sathya, S., & Rajendran, N. (2018). A study on sequential pattern mining on chemical information. International Journal of Engineering and Technology, 7(2.33), 532-535. https://doi.org/10.14419/ijet.v7i2.33.14828