Term Weight Measures Influence in Information Retrieval

  • Authors

    • K Pradeep Reddy VARDHAMAN COLLEGE OF ENGINEERING, JNTUH, HYDERABAD, INDIA
    • T Raghunadha Reddy
    • G Apparao Naidu
    • B Vishnu Vardhan
    2018-05-31
    https://doi.org/10.14419/ijet.v7i2.11664
  • Information Retrieval, Term Weight Measures, Tfidf, Recal, Cosine Similarity Measure

  • Abstract

    Indexing was majorly used in different applications like information retrieval (IR), Document categorization. In the field of IR, indexer is used by search engines to represent the content of a document with short and content-bearing terms so that the retrieval process obtained great performance. The text index systems produce better results based on the assignment of suitable weights to the terms. These results crucially depend on the selection of the efficient term weighting measures. In this work, the experimentation carried out with different types of term weight measures to assign weights to the terms in the query and document representation. Cosine similarity measure is used to find the similarity between the query vector and document vector. The experimentation is performed on four standard datasets and recall as a performance evaluation measure. The results obtained in this work are promising than most of the approaches in IR field.

     

     

  • References

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  • How to Cite

    Pradeep Reddy, K., Raghunadha Reddy, T., Apparao Naidu, G., & Vishnu Vardhan, B. (2018). Term Weight Measures Influence in Information Retrieval. International Journal of Engineering & Technology, 7(2), 832-836. https://doi.org/10.14419/ijet.v7i2.11664

    Received date: 2018-04-17

    Accepted date: 2018-05-14

    Published date: 2018-05-31