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Importance of Domain Knowledge in Web Recommender Systems

by Saloni Aggarwal, Veenu Mangat
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 16
Year of Publication: 2015
Authors: Saloni Aggarwal, Veenu Mangat
10.5120/ijca2015906643

Saloni Aggarwal, Veenu Mangat . Importance of Domain Knowledge in Web Recommender Systems. International Journal of Computer Applications. 127, 16 ( October 2015), 10-14. DOI=10.5120/ijca2015906643

@article{ 10.5120/ijca2015906643,
author = { Saloni Aggarwal, Veenu Mangat },
title = { Importance of Domain Knowledge in Web Recommender Systems },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 16 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 10-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number16/22812-2015906643/ },
doi = { 10.5120/ijca2015906643 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:18:11.344940+05:30
%A Saloni Aggarwal
%A Veenu Mangat
%T Importance of Domain Knowledge in Web Recommender Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 16
%P 10-14
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web usage data is extensively used in every domain to analyze the browsing behavior of the users who visited the website or search engines. Web usage data is contained in server logs called as Web Logs. This data enables the website owners to infer the needs and interests of the users for using this information to increase the revenue from their web business. The website owners employ recommender systems for this purpose. The recommender systems exploit web usage data to predict what web pages the user will visit next and therefore offer the recommendations for those very pages to the user and offers them support while browsing. This in turn helps users to have a better browsing experience, personalized support and hence, probability of user buying out the products from that website increases. Web usage mining alone is used in traditional recommender systems. Modern recommender systems employ semantic knowledge base i.e. domain knowledge in addition to web usage mining for efficient prediction of pages as this helps in avoiding the new page problem. This paper presents a comparative and comprehensive study of modern and traditional recommender systems.

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Index Terms

Computer Science
Information Sciences

Keywords

Semantic Knowledge Domain Knowledge Web Usage Data Personalized Services.

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