Review on Information Retrieval for Desktop Search Engine

  • Akshat Divya Akshay
  • Jammula Nikhil
  • Arindam Chowdhury
  • S. A. Karthik
Keywords: Information Retrieval, Query Understanding, Feature Extraction, Entity Recognition, Similarity Measures

Abstract

Search is an important aspect of information management often taken for granted. Domain specific repositories are growing in both size and numbers calling for efficient search and retrieval of documents. This paper explores the possible techniques and necessary system components for a search engine charting several iterative optimizations over the last few years. This paper focuses on NLP models while retaining basic principles from other methods that assist in information search.

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Author Biographies

Akshat Divya Akshay

Department of Information Science and Engineering. Dayananda Sagar Academy of Technology and Management Bangalore (DSATM Bangalore). Karnataka, India.

Jammula Nikhil

Department of Information Science and Engineering. Dayananda Sagar Academy of Technology and Management Bangalore (DSATM Bangalore). Karnataka, India.

Arindam Chowdhury

Department of Information Science and Engineering. Dayananda Sagar Academy of Technology and Management Bangalore (DSATM Bangalore). Karnataka, India.

S. A. Karthik

Department of Information Science and Engineering. Dayananda Sagar Academy of Technology and Management Bangalore (DSATM Bangalore). Karnataka, India.

This is an open access article, licensed under CC-BY-SA

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Published
        Views : 498
2020-06-02
    Downloads : 271
How to Cite
[1]
A. D. Akshay, J. Nikhil, A. Chowdhury, and S. A. Karthik, “Review on Information Retrieval for Desktop Search Engine”, International Journal of Education, Science, Technology, and Engineering, vol. 3, no. 1, pp. 19-25, Jun. 2020.
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Articles