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Introduction to special issue on recommender systems
John Riedl, Barry Smyth
Article No.: 1
Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems
Fidel Cacheda, Víctor Carneiro, Diego Fernández, Vreixo Formoso
Article No.: 2
The technique of collaborative filtering is especially successful in generating personalized recommendations. More than a decade of research has resulted in numerous algorithms, although no comparison of the different strategies has been made. In...
Using external aggregate ratings for improving individual recommendations
Akhmed Umyarov, Alexander Tuzhilin
Article No.: 3
This article describes an approach for incorporating externally specified aggregate ratings information into certain types of recommender systems, including two types of collaborating filtering and a hierarchical linear regression model. First, we...
Automatic tag recommendation algorithms for social recommender systems
Yang Song, Lu Zhang, C. Lee Giles
Article No.: 4
The emergence of Web 2.0 and the consequent success of social network Web sites such as Del.icio.us and Flickr introduce us to a new concept called social bookmarking, or tagging. Tagging is the action of connecting a relevant user-defined keyword...
The increasing availability of location-acquisition technologies (GPS, GSM networks, etc.) enables people to log the location histories with spatio-temporal data. Such real-world location histories imply, to some extent, users' interests in...