Hot News Recommendation System across Heterogonous Websites Using Hadoop

Abstract:

The current most news recommendations are suitable for news which comes from a single news website, not for news from different news websites. Little research work has been reported on utilizing hundreds of news websites to provide top hot news services for group customers (e.g. Government staffs). In this paper, we present hot news recommendation system based on Hadoop, which is from hundreds of different news websites. We discuss our news recommendation system architecture based on Hadoop.We conclude that Hadoop is an excellent tool for web big data analytics and scales well with increasing data set size and the number of nodes in the cluster. Experimental results demonstrate the reliability and effectiveness of our method.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 4704-4707
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.4704
• Online since: July 2014
• Authors: Sheng Wu Xu*, Zheng You Xia
• Keywords: Bayesian Mdoel, Bbig Datastyling, Hadoope, News Recommendation

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