ABSTRACT
No abstract available.
- D. Goldberg, D. Nichols, B. M. Oki, and D. Terry. Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35(12):61--70, 1992. Google ScholarDigital Library
- J. L. Herlocker, J. A. Konstan, A. Borchers, and J. Riedl. An algorithmic framework for performing collaborative filtering. In Proceedings of the 1999 Conference on Research and Development in Information Retrieval, Aug. 1999. Google ScholarDigital Library
- J. Kleinberg and D. Liben-Nowell. The link prediction problem for social networks. In Proceedings of the 12th International Conference on Information and Knowledge Management (CIKM), 2003. Google ScholarDigital Library
- J. M. Pujol, R. Sanguesa, and J. Delgado. Extracting reputation in multi agent systems by means of social network topology. In Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2002. Google ScholarDigital Library
- M. Richardson and P. Domingos. Mining knowledge-sharing sites for viral marketing. In Proceedings of the 8th International Conference on Knowledge Discovery and Data Mining (KDD), 2002. Google ScholarDigital Library
- E. M. Rogers. Diffusion of Innovations. Free Press, 2003.Google Scholar
Index Terms
- SNACK: incorporating social network information in automated collaborative filtering
Recommendations
An effective recommendation method for cold start new users using trust and distrust networks
Recommendation systems analyze the purchasing behavior (e.g., item ratings) of users to learn about their preferences and recommend products or services that may be of interest to them. However, as new users require time to become familiar with ...
A survey of collaborative filtering based social recommender systems
Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest to a user items that might be of interest to her. Recent studies demonstrate that information from social networks can be exploited to ...
Social network data to alleviate cold-start in recommender system
A Systematic Literature Review on Recommender Systems using social network data to mitigate the cold-start problem is executed.The method used in the Systematic Literature Review is exposed.Analysis of 666 papers and detailing of 20 papers considered ...
Comments