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Reseach Article

A Review on Current Recommendation Systems

by Shivani Sharma, Manish Dhir
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 13
Year of Publication: 2015
Authors: Shivani Sharma, Manish Dhir
10.5120/ijca2015907500

Shivani Sharma, Manish Dhir . A Review on Current Recommendation Systems. International Journal of Computer Applications. 131, 13 ( December 2015), 7-11. DOI=10.5120/ijca2015907500

@article{ 10.5120/ijca2015907500,
author = { Shivani Sharma, Manish Dhir },
title = { A Review on Current Recommendation Systems },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 13 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number13/23507-2015907500/ },
doi = { 10.5120/ijca2015907500 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:27:13.242919+05:30
%A Shivani Sharma
%A Manish Dhir
%T A Review on Current Recommendation Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 13
%P 7-11
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, E-commerce, web service and web information system have been used explosively. Massive explosion of the world-wide-web and the emergence of e- commerce have encouraged designers to develop recommendation systems. Web users demonstrate a variety of navigational patterns by clicking series of web pages. These patterns can be understood by mining user logs using WUM. One of the widely used applications of Web Usage Mining is Online Recommendation and prediction. Generally, all the recommendation systems follow a framework for generating efficient recommendations. Various recommendation systems use different approaches based on the sources of information they utilize. The accessible sources are user information (demographics), the product information (keywords, genres) and the user-item ratings. This paper gives introductive information about recommendation system, their techniques, and algorithms and also describes some existing works.

References
  1. Sneha Y.S, G. Mahadevan, Madhura, :An Online Recommendation System based on web usage mining and semantic web using LCS Algorithm”, IEEE 2011
  2. Sneha Y.S, G. Mahadevan, Madhura, : A Personalized Product Based Recommendation System Using Web Usage Mining and Semantic Web”, International Journal of Computer Theory and Engineering (IJCTE) Vol. 4, No. 2, April 2012
  3. Mehrdad Jalali1, Norwati Mustapha, Md. Nasir B Sulaiman, Ali Mamat, “A Web Usage Mining Approach Based on LCS Algorithm in Online Predicting Recommendation Systems” 12th International Conference Information Visualisation IEEE 2008.
  4. SuleymanSalim et al “Using Semantic Information for web usage mining based recommendation” International Conference IEEE 2009.
  5. Xin Sui, Suozhu Wang, Zhaowei Li “Research on the Model of Integration with Semantic Web and Agent Personalized Recommendation System “Proceedings of the 2009 13th International Conference on Computer Supported Cooperative Work in Design.
  6. A. Apostolico, “String editing and longest common subsequences”, Handbook of Formal Languages, Vol. 2. Linear Modeling: Background and Application, Springer Verlag, Berlin, chapter 8, 1997, pp. 361–398.
  7. RVVSV Prasad, V Valli Kumari “A Categorical Review of Recommender Systems” , International Journal of Distributed and Parallel Systems (IJDPS) Vol.3, No.5, September 2012 Hadi Khosravi Farsani, and Mohammadali Nematbakhsh “A Semantic Recommendation Procedure for Electronic Product Catalog”, World Academy of Science, Engineering and Technology 22 2006.
  8. Suguna, D, Sharmila, “Clustering Web log Files - A Review”, International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 4, April – 2013 ISSN: 2278- 0181
  9. Himangni Rathore, Hemant Verma, “Analysis on Recommended System for Web Information Retrieval Using HMM”, International Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, November 2014.
  10. R.Baraglia, F.Silvestri,” An online recommender system for large Web sites”, Web Intelligence, IEEE/WIC/ACM, 2004, pp. 20–24.
  11. Sneha Y S, G. Mahadevan, Madhura, “A Personalized Product Based Recommendation System Using Web Usage Mining and Semantic Web”, 2011 International Conference on Information and Computer Application (ICICA 2011).
  12. A. Singh and S. Sharma, “Role of Page ranking algorithm in Searching the Web: A Survey”, International Journal of Engineering & Technology, Management and Applied Sciences, Vol. 1, Issue 1, June 2014.
  13. P. Bari and P. M. Chawan. "Web Usage Mining", Journal of Engineering Computers & Applied Science, Vol. 2, No. 6, pp. 34-38, 2013
  14. R. Sharma and K. Kaur, "Review of Web Structure Mining Techniques using Clustering and Ranking Algorithms", International Journal of Research in Computer and Communication, IJRCCT, Vol. 3, No. 6, pp. 663-668, 2014.
  15. C. Tsai, C. Lai and M. Chiang, "Data mining for internet of things: A survey," IEEE Communication Surveys & Tutorials, Vol. 16, No. 1, 2014.
  16. F. S. Gharehchopogh and Z. A. Khalifelu, "Analysis and evaluation of unstructured data: text mining versus natural language processing" Application of Information and Communication Technologies (AICT), 2011 5th International Conference on. IEEE, pp. 1-4, 2011.
  17. C. Kaur, and R. R. Aggarwal, "Reference Scan Algorithm for Path Traversal Patterns.", International Journal of Computer Applications, Vol. 48. Pp no. 20-25, 2012
  18. V. Losarwar, M. Joshi, “Data Preprocessing in Web Usage Mining”, International Conference on Artificial Intelligence and Embedded Systems (ICAIES'2012), pp. 15-16, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Recommendation System Knowledge based systems Web Usage Mining.