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A novel method to Automatically Categorizing Search Results using Web Search Goals

by Rohini B. Mothe, V. S. Deshmukh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 22
Year of Publication: 2014
Authors: Rohini B. Mothe, V. S. Deshmukh
10.5120/17318-3899

Rohini B. Mothe, V. S. Deshmukh . A novel method to Automatically Categorizing Search Results using Web Search Goals. International Journal of Computer Applications. 98, 22 ( July 2014), 35-39. DOI=10.5120/17318-3899

@article{ 10.5120/17318-3899,
author = { Rohini B. Mothe, V. S. Deshmukh },
title = { A novel method to Automatically Categorizing Search Results using Web Search Goals },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 22 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number22/17318-3899/ },
doi = { 10.5120/17318-3899 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:01.146907+05:30
%A Rohini B. Mothe
%A V. S. Deshmukh
%T A novel method to Automatically Categorizing Search Results using Web Search Goals
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 22
%P 35-39
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In present days world wide web provides a platform for users to satisfy their information needs, for this purpose search engine tools are commonly used. Available search engine give result for a particular query in the form of flat rank list, which works well for non-ambiguous query. But,in case of ambiguous query which having multiple aspects the flat rank list not works well. So in such cases reorganization of search result is necessary. In this paper, proposed a method which reorganizes search result by analyzing user's implicit feedback. Based upon this feedback doing text processing, enriching each url by combination of title and snippet ,and mapping these data to Pseudo-document. Pseudo-document contain set of keywords which are different aspects of query. And then performing clustering on these pseudo-document using fuzzy k-mean clustering. And these clusters contain links which are most relevant to each other. Also rearranging results based upon most visited links such that it should occur at topmost. And this reorganization will increase the performance and evaluation of search engine. And the cluster labels.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy k-means clustering Implicit feedback Pseudo-documents User search goals.

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