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Clustering and Recommendation using WordNet

by Justina G. Nadar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 14
Year of Publication: 2015
Authors: Justina G. Nadar
10.5120/19732-1520

Justina G. Nadar . Clustering and Recommendation using WordNet. International Journal of Computer Applications. 112, 14 ( February 2015), 9-12. DOI=10.5120/19732-1520

@article{ 10.5120/19732-1520,
author = { Justina G. Nadar },
title = { Clustering and Recommendation using WordNet },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 14 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number14/19732-1520/ },
doi = { 10.5120/19732-1520 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:27.161607+05:30
%A Justina G. Nadar
%T Clustering and Recommendation using WordNet
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 14
%P 9-12
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The recommender systems are new type of software tools designed to help users find their way through today's online shops. Due to the increasing number of e-commerce websites, it is necessary to render effective recommendation to the users. Here we present an overview of current recommendation systems and then our proposed system that employs WordNet dictionary in clustering and content based filtration to provide tailored and friendly suggestions to the user. The proposed system is a user-centric approach that analyses the navigation path of the user and clusters the keyword extracted from WordNet to recommend user articles.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Recommender systems WordNet Clustering Advanced Kmeans

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