@article {10.3844/jcssp.2010.748.755,
article_type = {journal},
title = {Feature Analysis of Recommender Techniques Employed in the Recommendation Engines},
author = {Ganapathy, Gopinath and Arunesh, P. K.},
volume = {6},
number = {7},
year = {2010},
month = {Jul},
pages = {748-755},
doi = {10.3844/jcssp.2010.748.755},
url = {https://thescipub.com/abstract/jcssp.2010.748.755},
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 = {Journal of Computer Science},
publisher = {Science Publications}
}