Onto based cluster labelling and incremental system for information retrieval

  • Authors

    • Seifedine Kadry Beirut Arab University
    • Irfan Ahamed Mohammed Saleem Hindusthan College of Engineering and Technology
    • Lakshmana Kumar Ramasamy Nehru Institute of Engineering and Technology
    • N. Kannammal Surya Engineering College
    2019-04-12
    https://doi.org/10.14419/ijet.v7i4.22914
  • Semantic Document Clustering, K-Means, Labels, Synsets.

  • Abstract

    Document clustering is utilised for data retrieval, past task of labels to cluster individuals enhances quick retrieval, and Existing framework doles out labels because of standard terms show in archives. However, semantic marks are first taking into Document semantic relationship, the incremental calculation for the versatile framework. The proposed work allocates onto mark because of scientific categorisation, i.e. ontology-based; word net Synsets and gleams coordinating and incremental dynamicity is accomplished through naming. The assessment is done utilising f-measure and figuring speed, contrasted and benchmark K-Means, K-Means without labels. Thus semantic labelling is designed more efficient than traditional document clustering methodologies and can be implemented for real-time internet document clustering applications.

     

     


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  • How to Cite

    Kadry, S., Ahamed Mohammed Saleem, I., Kumar Ramasamy, L., & Kannammal, N. (2019). Onto based cluster labelling and incremental system for information retrieval. International Journal of Engineering & Technology, 7(4), 5699-5704. https://doi.org/10.14419/ijet.v7i4.22914

    Received date: 2018-12-02

    Accepted date: 2019-03-29

    Published date: 2019-04-12