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Information Retrieval in Search Engines Using Pseudo Relevance Feedback Mechanism

B. M,R. M P,E. G S R

Published 2019 in 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN)

ABSTRACT

Online data generation is increasing rapidly due to technological development. In order to handle the huge volume of data, big data methodology is used widely. Though big data can able to process huge data, it has its own issues including information storage, data management, and retrieving data. In big data, data retrieval is an issue where the method of data retrieval and implementation environment differs. Though data mining has become evolving technology, it requires an optimal retrieval mechanism to extract data from the hugerepository.Therefore, an information retrieval method which in turn should effectively perform data retrieval in terms of both speed and accuracy need to be implemented. Topic relevance mechanism is used to retrieve an appropriate document from the repository, these documents are then ranked based on user preference using pseudo-relevance feedback mechanism. And hence the accuracy of the retrieved document is improved.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN)

  • Publication date

    2019-03-01

  • Fields of study

    Not labeled

  • Identifiers
    DOI 10.1109/ViTECoN.2019.8899424
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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  • No concepts are published for this paper.

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