A Framework for Collaborative, Content-Based and Demographic Filtering von Pazzani, Michael J

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Detecting Group Differences: Mining Contrast Sets von Bay, Stephen D, Pazzani, Michael J

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User Modeling for Adaptive News Access von Billsus, Daniel, Pazzani, Michael J

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Machine Learning for User Modeling von Webb, Geoffrey I, Pazzani, Michael J, Billsus, Daniel

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A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases von Keogh, Eamonn J., Pazzani, Michael J.

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Content-Based Recommendation Systems von Pazzani, Michael J., Billsus, Daniel

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A Principal Components Approach to Combining Regression Estimates von Merz, Christopher J, Pazzani, Michael J

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Influence of Prior Knowledge on Concept Acquisition: Experimental and Computational Results von Pazzani, Michael J

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Application of an expert system in the management of HIV-infected patients von PAZZANI, M. J, SEE, D, SCHROEDER, E, TILLES, J

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Two-Stage Machine Learning model for guideline development von Mani, Subramani, Shankle, William R, Dick, Malcolm B, Pazzani, Michael J

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Learning probabilistic user profiles: applications for finding interesting Web sites, notifying users of relevant changes to Web pages, and locating grant opportunities von Ackerman, Mark, Billsus, Daniel, Gaffney, Scott, Hettich, Seth, Khoo, Gordon, Kim, Dong Joon, Klefstad, Ray, Lowe, Charles, Ludeman, Alexius, Muramatsu, Jack, Omori, Kazuo, Pazzani, Michael J, Semler, Douglas, Starr, Brian, Yap, Paul

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Commercial Applications of Machine Learning for Personalized Wireless Portals von Pazzani, Michael J.

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Collaborative Filtering with the Simple Bayesian Classifier von Miyahara, Koji, Pazzani, Michael J.

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Adaptive News Access von Billsus, Daniel, Pazzani, Michael J.

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Error reduction through learning multiple descriptions von Ali, Kamal M., Pazzani, Michael J.

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Knowledge‐Based Avoidance of Drug‐Resistant HIV Mutants von Lathrop, Richard H., Steffen, Nicholas R., Raphael, Miriam P., Deeds‐Rubin, Sophia, Pazzani, Michael J., Cimoch, Paul J., See, Darryl M., Tilles, Jeremiah G.

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Knowledge discovery from data? von Pazzani, Michael J

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Scaling up Dynamic Time Warping to Massive Datasets von Keogh, Eamonn J., Pazzani, Michael J.

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Adjusted probability Naive Bayesian induction von Webb, Geoffrey I., Pazzani, Michael J.

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Exploring the Decision Forest: An Empirical Investigation of Occam's Razor in Decision Tree Induction von Murphy, P. M., Pazzani, M. J.

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