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Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

A. Popescul, L. Ungar, D. Pennock, and S. Lawrence. CoRR, (2013)

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Cluster-based concept invention for statistical relational learning.A. Popescul, and L. Ungar. KDD, page 665-670. ACM, (2004)Predictive Crawling for Commercial Web Content.S. Han, B. Brodowsky, P. Gajda, S. Novikov, M. Bendersky, M. Najork, R. Dua, and A. Popescul. WWW, page 627-637. ACM, (2019)Methods and metrics for cold-start recommendations.A. Schein, A. Popescul, L. Ungar, and D. Pennock. SIGIR, page 253-260. ACM, (2002)Quick Access: Building a Smart Experience for Google Drive.S. Tata, A. Popescul, M. Najork, M. Colagrosso, J. Gibbons, A. Green, A. Mah, M. Smith, D. Garg, C. Meyer and 1 other author(s). KDD, page 1643-1651. ACM, (2017)Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data EnvironmentsA. Popescul, L. Ungar, D. Pennock, and S. Lawrence. CoRR, (2013)Linear prediction models with graph regularization for web-page categorization.T. Zhang, A. Popescul, and B. Dom. KDD, page 821-826. ACM, (2006)CROC: A New Evaluation Criterion for Recommender Systems.A. Schein, A. Popescul, L. Ungar, and D. Pennock. Electron. Commer. Res., 5 (1): 51-74 (2005)Clustering and Identifying Temporal Trends in Document Databases.A. Popescul, G. Flake, S. Lawrence, L. Ungar, and C. Giles. ADL, page 173-182. IEEE Computer Society, (2000)Statistical Relational Learning for Document Mining.A. Popescul, L. Ungar, S. Lawrence, and D. Pennock. ICDM, page 275-282. IEEE Computer Society, (2003)Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments.A. Popescul, L. Ungar, D. Pennock, and S. Lawrence. UAI, page 437-444. Morgan Kaufmann, (2001)

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Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

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Disambiguation of "Popescul, Alexandrin"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

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Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments