Recommender Systems: Increasing Profits and Efficiency in Business
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2014 by IJETT Journal | ||
| Volume-16 Number-3 |
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| Year of Publication : 2014 | ||
| Authors : Charlotte Castelino , Reena Shaw Muthalaly , Aloma Lopes , Sweedal Lopes |
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 10.14445/22312803/IJETT-V16P124 |
Citation
Charlotte Castelino , Reena Shaw Muthalaly , Aloma Lopes , ,Sweedal Lopes. "Recommender Systems: Increasing Profits and Efficiency in Business", International Journal of Engineering Trends and Technology (IJETT), V16(3),119-123 Oct 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
Today, in almost every field, when interacting with a computer or any other automated device, we are provided recommendations or suggestions of possible preferences related to a product or a service. These applications make use of recommender systems to entice users toward a particular product and increase user association with the application. In this paper, we present a detailed study on recommender system and their new features.
References
[1]http://www.practicalecommerce.com/articles/1942-10-Questions-on-Product-Recommendations
[2]http://inside-bigdata.com/2014/10/01/ask-data-scientist-recommender-systems/
[3]http://technocalifornia.blogspot.in/2014/08/introduction-to-recommender-systems-4.html
[4] http://vikas.sindhwani.org/recommender.pdf
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[8] http://mahout.apache.org/
[9]http://www.cognizant.com/InsightsWhitepapers/How-to-Develop-Online-Recommendation-Systems-that-Deliver-Superior-Business-Performance
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Keywords
Recommender systems, collaborative filtering, social media, content-based filtering, Apache Mahout