Recommender Systems: Increasing Profits and Efficiency in Business

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)
  
© 2014 by IJETT Journal
Volume-16 Number-3
Year of Publication : 2014
Authors : Charlotte Castelino , Reena Shaw Muthalaly , Aloma Lopes , Sweedal Lopes
  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
[5] Y. Bengio, A. Courville, and P. Vincent., "Representation Learning: A Review and New Perspectives," IEEE Trans. PAMI, special issue Learning Deep Architectures, 2013
[6]readwrite.com/2009/1/28/5_problems_of_recommender_systems
[7] Shyong K. Lam and John Riedl. Shilling recommender systems for fun and profit. In WWW ’04: Proceedings of the 13th international conference on World Wide Web, pages 393–402, New York, NY, USA, 2004. ACM.
[8] http://mahout.apache.org/
[9]http://www.cognizant.com/InsightsWhitepapers/How-to-Develop-Online-Recommendation-Systems-that-Deliver-Superior-Business-Performance
[10] {R}icci, {F}., {R}okach, {L}., {S}hapira, {B}., {K}antor {B}. {P}. (2011). "Recommender systems handbook". Recommender Systems Handbook (Springer): 1–35.
[11] Recommender Systems using Social Network Analysis: Challenges and Future Trends Johann Stan 1, Fabrice Muhlenbach 2, Christine Largeron

Keywords
Recommender systems, collaborative filtering, social media, content-based filtering, Apache Mahout