Research Article Open Access

Feature Analysis of Recommender Techniques Employed in the Recommendation Engines

Gopinath Ganapathy and P. K. Arunesh

Abstract

Problem statement: Recommender Systems (RS) have become a widely researched area as it is extensively used in web usage mining and E-commerce platforms. Approach: There were a number of recommender systems available to suggest the web pages for the web users. Results: A recommender system acted as an intelligent intermediary that automatically generates and predicts information and web pages, which suit the users’ behavior and users’ needs. Conclusion: The various recommender models and analyzing the key features of those models and analyzing the features of portal sites that employ recommender systems to help the research community are the key features of this study and survey.

Journal of Computer Science
Volume 6 No. 7, 2010, 748-755

DOI: https://doi.org/10.3844/jcssp.2010.748.755

Submitted On: 23 April 2010 Published On: 31 July 2010

How to Cite: Ganapathy, G. & Arunesh, P. K. (2010). Feature Analysis of Recommender Techniques Employed in the Recommendation Engines. Journal of Computer Science, 6(7), 748-755. https://doi.org/10.3844/jcssp.2010.748.755

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Keywords

  • Recommender systems
  • recommendation engines
  • estimation methods
  • extensions to recommender systems