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Ordered Frequent Itemsets Matrix Based On Fp-Tree Structure And Apriori Algorithm

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Evaluating the Effectiveness of Web Search Metrics

by J. Jayanthi, M. Ezhilmathi, S. Rathi
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 10
Year of Publication: 2012
Authors: J. Jayanthi, M. Ezhilmathi, S. Rathi
10.5120/ijais12-450818

J. Jayanthi, M. Ezhilmathi, S. Rathi . Evaluating the Effectiveness of Web Search Metrics. International Journal of Applied Information Systems. 4, 10 ( December 2012), 28-35. DOI=10.5120/ijais12-450818

@article{ 10.5120/ijais12-450818,
author = { J. Jayanthi, M. Ezhilmathi, S. Rathi },
title = { Evaluating the Effectiveness of Web Search Metrics },
journal = { International Journal of Applied Information Systems },
issue_date = { December 2012 },
volume = { 4 },
number = { 10 },
month = { December },
year = { 2012 },
issn = { 2249-0868 },
pages = { 28-35 },
numpages = {9},
url = { https://www.ijais.org/archives/volume4/number10/396-0818/ },
doi = { 10.5120/ijais12-450818 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:48:11.271201+05:30
%A J. Jayanthi
%A M. Ezhilmathi
%A S. Rathi
%T Evaluating the Effectiveness of Web Search Metrics
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 10
%P 28-35
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software metrics are the key performance indicators, using which the performance of a system can be assessed quantitatively. Metrics can also be applied for personalized web search which can be used to retrieve relevant results for each individual user depending on their unique profile. Although personalized search based on user profile has been under research for many years and various metrics have been proposed, it is still uncertain whether personalization is unswervingly effective on different queries for different user profiles. A framework for personalized search which retrieves result based on user profile has been presented in this paper. User profile is maintained in the form of preference network (PN). Further metrics for ranking the search results based on user profile is also proposed.

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Index Terms

Computer Science
Information Sciences

Keywords

Personalization user profile preference network

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