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Multidimensional User Data Model for Web Personalization

by Nithin K. Anil, Sharath Basil Kurian, Aby Abahai T., Surekha Mariam Varghese
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 12
Year of Publication: 2013
Authors: Nithin K. Anil, Sharath Basil Kurian, Aby Abahai T., Surekha Mariam Varghese
10.5120/11896-7955

Nithin K. Anil, Sharath Basil Kurian, Aby Abahai T., Surekha Mariam Varghese . Multidimensional User Data Model for Web Personalization. International Journal of Computer Applications. 69, 12 ( May 2013), 32-37. DOI=10.5120/11896-7955

@article{ 10.5120/11896-7955,
author = { Nithin K. Anil, Sharath Basil Kurian, Aby Abahai T., Surekha Mariam Varghese },
title = { Multidimensional User Data Model for Web Personalization },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 12 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number12/11896-7955/ },
doi = { 10.5120/11896-7955 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:31:38.910492+05:30
%A Nithin K. Anil
%A Sharath Basil Kurian
%A Aby Abahai T.
%A Surekha Mariam Varghese
%T Multidimensional User Data Model for Web Personalization
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 12
%P 32-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Personalization is being applied to great extend in many systems. This paper presents a multi-dimensional user data model and its application in web search. Online and Offline activities of the user are tracked for creating the user model. The main phases are identification of relevant documents and the representation of relevance and similarity of the documents. The concepts Keywords, Topics, URLs and clusters are used in the implementation. The algorithms for profiling, grading and clustering the concepts in the user model and algorithm for determining the personalized search results by re-ranking the results in a search bank are presented in this paper. Simple experiments for evaluation of the model and their results are described.

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Index Terms

Computer Science
Information Sciences

Keywords

Knowledge Management Personalized Systems Web Services World Wide Web

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