Feature Analysis of Recommender Techniques Employed in the Recommendation Engines
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.
DOI: https://doi.org/10.3844/jcssp.2010.748.755
Copyright: © 2010 Gopinath Ganapathy and P. K. Arunesh. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Recommender systems
- recommendation engines
- estimation methods
- extensions to recommender systems