Crowdsourcing MapReduce: JSMapReduce
Proceedings of the 22nd international conference on World Wide Web companion
Hi-index | 0.00 |
The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users隆炉 interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Delicious website.