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Optimization of User Query for Improving Document Retrieval Performance

by Nidhi Bhandari, Rachna Navalakhe, G.L. Prajapati
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 2
Year of Publication: 2022
Authors: Nidhi Bhandari, Rachna Navalakhe, G.L. Prajapati
10.5120/ijca2022921970

Nidhi Bhandari, Rachna Navalakhe, G.L. Prajapati . Optimization of User Query for Improving Document Retrieval Performance. International Journal of Computer Applications. 184, 2 ( Mar 2022), 14-19. DOI=10.5120/ijca2022921970

@article{ 10.5120/ijca2022921970,
author = { Nidhi Bhandari, Rachna Navalakhe, G.L. Prajapati },
title = { Optimization of User Query for Improving Document Retrieval Performance },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2022 },
volume = { 184 },
number = { 2 },
month = { Mar },
year = { 2022 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number2/32304-2022921970/ },
doi = { 10.5120/ijca2022921970 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:23.943489+05:30
%A Nidhi Bhandari
%A Rachna Navalakhe
%A G.L. Prajapati
%T Optimization of User Query for Improving Document Retrieval Performance
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 2
%P 14-19
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The unstructured data processing and finding accurate information from IR models is a complex task. The classical techniques use different concepts for improving IR models such as categorization, classification and many more. This paper reviews different document retrieval techniques first and then an extension on previously introduced version is provided. Similar to the traditional model, this technique first pre-process data and extract features. After that the retrieved features are organized in a tuple. These tuples are further used with fuzzy c means algorithm to cluster their domain according to their features. This process reduces the time of proposed search model. In addition to that, for preventing inappropriate query submission, the new query generation and optimization is also proposed in this work. The results with the different dataset shows the proposed IR model improve the performance in terms of efficiency and accuracy.

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Index Terms

Computer Science
Information Sciences

Keywords

Text mining Query optimization Semantic knowledge Information retrieval c-means clustering