Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Laplacian Eigenmaps for dimensionality reduction and data representation
Neural Computation
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Diffusion Kernels on Statistical Manifolds
The Journal of Machine Learning Research
IEEE Transactions on Knowledge and Data Engineering
Digital Content Recommender on the Internet
IEEE Intelligent Systems
DiffusionRank: a possible penicillin for web spamming
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Mining social networks using heat diffusion processes for marketing candidates selection
Proceedings of the 17th ACM conference on Information and knowledge management
SoRec: social recommendation using probabilistic matrix factorization
Proceedings of the 17th ACM conference on Information and knowledge management
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Using a trust network to improve top-N recommendation
Proceedings of the third ACM conference on Recommender systems
Training and testing of recommender systems on data missing not at random
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A matrix factorization technique with trust propagation for recommendation in social networks
Proceedings of the fourth ACM conference on Recommender systems
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Mining Web Graphs for Recommendations
IEEE Transactions on Knowledge and Data Engineering
On top-k recommendation using social networks
Proceedings of the sixth ACM conference on Recommender systems
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Growth of the internet has lead to information overload. Recommender systems filter this vast amount of information and outputs useful information. They are traditionally based on users rating of items. But those systems were not useful for coldstart users i.e. users who have made very few purchases. So social recommenders began to evolve which makes use of social networks to improve recommendations. In this paper we propose a nearest neighbour based top N recommendation technique using social network. We model the data sources as graph and use heat diffusion process for generating recommendations. The experimental evaluation on the epinions dataset shows that our approach outperforms the approach that combines user based collaborative filtering approach and trust based approach.