Methods and Metrics for Cold-Start Recommendations (2002)

by Andrew I. Schein , Alexandrin Popescul , Lyle H. Ungar , David M. Pennock
Venue:PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL
Citations:164 - 7 self

Active Bibliography

3 CROC: A New Evaluation Criterion for Recommender Systems – Andrew I. Schein, Alexandrin Popescul, Lyle H. Ungar, David M. Pennock
16 Generative Models for Cold-Start Recommendations – Andrew I. Schein, Alexandrin Popescul, Lyle H. Ungar, David M. Pennock - 2001
15 Jumping Connections: A Graph-Theoretic Model for Recommender Systems – Batul J. Mirza - 2001
733 Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions – Gediminas Adomavicius, Alexander Tuzhilin - 2005
133 Probabilistic models for unified collaborative and content-based recommendation in sparsedata environments – Rin Popescul, Lyle H. Ungar - 2001
566 Evaluating collaborative filtering recommender systems – Jonathan L. Herlocker, Joseph A. Konstan, Loren G. Terveen, John, T. Riedl - 2004
1 A Taxonomy of Collaborative-Based Recommender Systems – Fabián P. Lousame, Eduardo Sánchez - 2009
2 Evaluating Recommendation Algorithms by Graph Analysis – Batul J. Mirza, Benjamin J. Keller, Naren Ramakrishnan - 2001
24 Studying Recommendation Algorithms by Graph Analysis – Batul J. Mirza, Naren Ramakrishnan, Benjamin J. Keller - 2003
21 Probabilistic Memory-based Collaborative Filtering – Kai Yu, Anton Schwaighofer, Volker Tresp, Xiaowei Xu, Hans-peter Kriegel
Chapter 4 A Comprehensive Survey of Neighborhood-based Recommendation Methods – Christian Desrosiers, George Karypis
4 Meeting User Information Needs in Recommender Systems – Sean Michael McNee - 2006
14 Applying collaborative filtering techniques to movie search for better ranking and browsing – Seung-taek Park, David M. Pennock, Dennis Decoste - 2007
SHAHANA SEN – Gediminas Adomavicius, Alexander Tuzhilin
123 Incorporating Contextual Information in Recommender Systems Using a Multidimensional Approach – Gediminas Adomavicius, Ramesh Sankaranarayanan, Shahana Sen, Alexander Tuzhilin - 2005
The Advantage of Careful Imputation Sources in Sparse Data-Environment of Recommender Systems: Generating Improved SVD-based Recommendations – Mustansar Ali Ghazanfar, Adam Prugel-bennett - 2012
Item-Based Top-N Recommendation Algorithms – Mukund Deshp, George Karypis, Mukund Deshp, George Karypis
Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments – David M. Pennock, Steve Lawrence, Rin Popescul, Lyle H. Ungar
53 A Taxonomy of Recommender Agents on the Internet – Miquel Montaner, Beatriz López, Josep Lluís de la Rosa - 2003