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Development of Hybrid Intelligent based Information Retreival Technique

by Gregory Gabriel James, Abugor Ejaita Okpako, C. Ituma, J.E. Asuquo
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 34
Year of Publication: 2022
Authors: Gregory Gabriel James, Abugor Ejaita Okpako, C. Ituma, J.E. Asuquo
10.5120/ijca2022922401

Gregory Gabriel James, Abugor Ejaita Okpako, C. Ituma, J.E. Asuquo . Development of Hybrid Intelligent based Information Retreival Technique. International Journal of Computer Applications. 184, 34 ( Oct 2022), 1-13. DOI=10.5120/ijca2022922401

@article{ 10.5120/ijca2022922401,
author = { Gregory Gabriel James, Abugor Ejaita Okpako, C. Ituma, J.E. Asuquo },
title = { Development of Hybrid Intelligent based Information Retreival Technique },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2022 },
volume = { 184 },
number = { 34 },
month = { Oct },
year = { 2022 },
issn = { 0975-8887 },
pages = { 1-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number34/32533-2022922401/ },
doi = { 10.5120/ijca2022922401 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:23:07.416748+05:30
%A Gregory Gabriel James
%A Abugor Ejaita Okpako
%A C. Ituma
%A J.E. Asuquo
%T Development of Hybrid Intelligent based Information Retreival Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 34
%P 1-13
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To find information over the internet to a certain level, depends on our capacity to track all related subjects and classify them into bunches of comparative themes. As the domain of information is enlarging over the internet , the time consumption and the difficulties experienced by researchers to find a relevant material that meets the user’s specified request increases, thereby putting the researchers into a state of dilemma at the cause of searching for relevant information that meets their need. The pursuit to trim down the challenges of impasse faced by researchers as well as time exhausted to filter relevant materials in the pools of irrelevant materials have motivated this research. The work aims at developing a Neuro-fuzzy intelligent search framework for tracking and recovery of web archives. The method used was Object-Oriented analysis and Design (OOAD). A hybrid intelligent framework – based tracking system was utilized as the finest choice for tracking archives, since the shortcomings of Neural Network and Fuzzy Logic based tracking system were complemented while their individual qualities are upgraded. This paper expands prior Fuzzy-based information retrieval approaches through increasing the Fuzzy variables and their linguistic values by utilizing distinctive rules and functions that characterized the record. The mapping of input to output parameters was achieved by applying the triangular membership’s functions. Adaptive neural fuzzy inference system model also utilized the Takagi Sugeno inference mechanism. It was observed that using ANFIS improved the hybrid intelligent framework – based tracking system performance slightly with 0.22641 representing 22.64% over the Fuzzy Inference System (FIS) results, thereby guarantee retrieval of most relevant documents that met the user’s request.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Intelligence ANFIS model Neuro-fuzzy Geno Method

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