Trends, problems and solutions of recommender system

Author

Jain, Sarika ; Grover, Anjali ; Thakur, Praveen Singh ; Choudhary, Sourabh Kumar

Author_Institution

Dept. of Comput. Applic., Nat. Inst. of Technol. Kurukshetra, Kurukshetra, India

fYear

2015

fDate

15-16 May 2015

Firstpage

955

Lastpage

958

Abstract

In this era of web, we have a huge amount of information overloaded over Internet. It becomes a herculean task for the user to get the relevant information. To some extent, the problem is being solved by the search engines, but they do not provide the personalization of data. So, to further filter the information, we need a recommendation engine. In this paper, we have described the various web recommender systems in use by some popular web sites on the internet like Amazon.com, LinkedIn.com, and YouTube.com etc. Further, we have described the various approaches used in the various recommender systems such as Content based, Collaborative and Hybrid recommender system. At the end of this paper, we focus on some of the main challenges faced by the web recommender systems and analyze some techniques to overcome them.

Keywords

Internet; information retrieval; recommender systems; search engines; Amazon.com; Internet; LinkedIn.com; Web recommender systems; YouTube.com; collaborative recommender system; content based recommender system; data personalization; hybrid recommender system; recommendation engine; relevant information; search engines; Automation; Collaboration; Correlation; Internet; Recommender systems; YouTube; Collaborative Recommender System; Content Based; Hybrid Recommender System; Recommender System;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communication & Automation (ICCCA), 2015 International Conference on

Conference_Location

Noida

Print_ISBN

978-1-4799-8889-1

Type

conf

DOI

10.1109/CCAA.2015.7148534

Filename

7148534