Advanced Overlap Community Detection by Associative Rule Mining and Multi-View Ant Clustering

  • Authors

    • T P.Latchoumi
    • Latha Parthiba
    • T P.Ezhilarasi
    • Golda Dilip
    • Hema Bhargavi
    https://doi.org/10.14419/ijet.v7i3.34.19588

    Received date: September 12, 2018

    Accepted date: September 12, 2018

    Published date: April 19, 2026

  • Clustering, Association Rule, Data Mining, Recommendation system.

  • Abstract

    Recommendation systems mean based on customers interest techniques and tools are to generate the new products and services. The main issue in this recommendation system is the number of users are more and giving preference to their items takes more time. And also processing the date takes more time. Hence, clustering techniques are used for users into overlapping groups helps in the information sparsely issue and improve recommendation range. Next essential factor in this system is dynamic attention on users in which their importance varies. This work mainly concentrates on using the ant clustering technique to improvethe multi-view clustering method.

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  • How to Cite

    P.Latchoumi, T., Parthiba, L., P.Ezhilarasi, T., Dilip, G., & Bhargavi, H. (2026). Advanced Overlap Community Detection by Associative Rule Mining and Multi-View Ant Clustering. International Journal of Engineering and Technology, 7(3.34), 913-917. https://doi.org/10.14419/ijet.v7i3.34.19588