Improving Information Retrieval Performance

Authors

  • Abhay Dwivedi  Department of BCA, Shri L.B.S. Degree College, Gonda, Uttar Pradesh, India
  • Ankit Maurya  Department of Mathematics, Shri L.B.S. Degree College, Gonda, Uttar Pradesh, India
  • Sandhya Rawat  I.E.T Dr. R.M.L.A. University Ayodhya, Uttar Pradesh, India

Keywords:

Information Retrival (IR), meta search engine, rank aggregation

Abstract

Locating interesting information is one of the most important tasks in Information Retrieval (IR). An IR system accepts a query from a user and responds with a set of documents. Generally, the system returns both relevant and non-relevant material and a document organization approach are applied to assist the user in finding the relevant information in the retrieved set. The two most widely used document organization approaches are the ranked list and clustering of the retrieved documents. Both these techniques have their strengths and weaknesses. This paper addresses the problem of offering scalable, adaptive, efficient, full-fledged information retrieval method. We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking functions, selecting documents based on multiple criteria, and improving search precision through word associations. We develop a set of techniques for the rank aggregation problem and compare their performance to that of well-known methods. A primary goal of our work is to design rank aggregation techniques for providing robustness of search in the context of web.

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Published

2022-10-30

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Section

Research Articles

How to Cite

[1]
Abhay Dwivedi, Ankit Maurya, Sandhya Rawat, " Improving Information Retrieval Performance" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.52-63, September-October-2022.