CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
Reseach Article

A Study on Swarm Intelligence Techniques in Recommender System

Published on February 2013 by V. Diviya Prabha, R. Rathipriya
International Conference on Research Trends in Computer Technologies 2013
Foundation of Computer Science USA
ICRTCT - Number 4
February 2013
Authors: V. Diviya Prabha, R. Rathipriya
a8c2afac-069b-4a80-8044-7f9abeda3fa0

V. Diviya Prabha, R. Rathipriya . A Study on Swarm Intelligence Techniques in Recommender System. International Conference on Research Trends in Computer Technologies 2013. ICRTCT, 4 (February 2013), 32-34.

@article{
author = { V. Diviya Prabha, R. Rathipriya },
title = { A Study on Swarm Intelligence Techniques in Recommender System },
journal = { International Conference on Research Trends in Computer Technologies 2013 },
issue_date = { February 2013 },
volume = { ICRTCT },
number = { 4 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 32-34 },
numpages = 3,
url = { /proceedings/icrtct/number4/10830-1049/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Research Trends in Computer Technologies 2013
%A V. Diviya Prabha
%A R. Rathipriya
%T A Study on Swarm Intelligence Techniques in Recommender System
%J International Conference on Research Trends in Computer Technologies 2013
%@ 0975-8887
%V ICRTCT
%N 4
%P 32-34
%D 2013
%I International Journal of Computer Applications
Abstract

Swarm intelligence deals with natural and artificial system provides an efficient way for finding optimal solution. During the past few decades researches are trying to use these techniques to solve many problems in various fields. Recommender system is the one of the most important application of E-Commerce and it plays vital role in understanding the users' behavior or interest by which it increases the profit of sales or usage of services of a web site. This paper describes a study on swarm intelligence techniques to find the optimal solution and based on that recommendation process is done.

References
  1. Abdurrahman et. al. , Classification of web user in web usage mining using ant colony optimization algorithm, Doctor Dissertation, Institute of technology, 2009.
  2. Ang X. S. , (2010b). Nature-Inspired Metaheuristic Algorithms, 2nd Edition, Luniver Press, UK.
  3. Ang X. S. and Deb S. (2010a) Engineering Optimization by Cuckoo Search, Int. J. Math. Modelling &Num. Optimization, Vol. 1, 330-343.
  4. Magdalini Eirinaki and Michalis Vazirgiannis, 2003. Web Mining for Web Personalization, ACM Transaction on Internet Technology, Vol. 3, No. 1, pp. 1-27.
  5. J. Kennedy, R. Eberhart, 1995. Particle Swarm Optimization, IEEE International Conference on Neural Network, Vol. 4, pp. 1942-1948.
  6. Ujjin, S. and Bentley, P. J . 2002. Learning User Preference Using Evolution. In Proceeding of the 4th Asia- Pacific Conference on Simulated Evolution and Learning. Singapore.
  7. Abdurrahman et al. , Classification of web user in web usage mining for analyzing unique behavior of web user, International Conference on Electrical Engineering and Informatics, 2007, pp. 356- 359.
  8. N Golovin, E. Rahm: Reinforcement learning Architecture for Web Recommendation, Proceedings on Information System.
Index Terms

Computer Science
Information Sciences

Keywords

Recommender System Swarm Intelligence Techniques Natural Inspired Techniques E-commerce