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John T. Riedl

University of Notre Dame

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Publication

Featured researches published by John T. Riedl.

IEEE Computer Graphics and Applications | 1998

Principles for information visualization spreadsheets

Ed H. Chi; John T. Riedl; Phillip J. Barry; Joseph A. Konstan

The visualization spreadsheet provides a framework for exploring large and complex data sets. Structuring user interactions using a spreadsheet paradigm creates a powerful tool for information visualization.

Archive | 2006

Accurate is not always good: How Accuracy Metrics have hurt Recommender Systems

Sean M. McNee; John T. Riedl; Joseph A. Konstan

Archive | 1998

Jump-starting movielens: user benefits of starting a collaborative filtering system with "dead data

B. J. Dahlen; Joseph A. Konstan; Jonathan L. Herlocker; Nathaniel Good; Al Borchers; John T. Riedl

Archive | 1996

Efficiency of shared-memory multiprocessors for a genetic sequence similarity search algorithm

Ed H. Chi; Elizabeth Shoop; John V. Carlis; Ernest F. Retzel; John T. Riedl

Archive | 2000

System, method, and article of manufacture for recommending items to users based on user preferences

Badrul Munir Sarwar; V. Nathaniel S. Good; John Benjamin Schafer; Bradley N. Miller; Joseph A. Konstan; Jonathan L. Herlocker; Albert T. Borchers; John T. Riedl

Archive | 1999

System, method and article of manufacture for making high user value recommendations

Paul Bieganski; Joseph A. Konstan; John T. Riedl

Metalens: a framework for multi-source recommendations | 2001

Metalens: a framework for multi-source recommendations

John Benjamin Schafer; Joseph A. Konstan; John T. Riedl

Archive | 1999

RS in E-Commerce

J. Ben Schafer; Joseph A. Konstan; John T. Riedl

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science | 2013

Radiology Diagnostic Exchange Agents: Clinical Term Identification and Validation

Kenneth Shores; Joseph A. Konstan; John T. Riedl; Andrew J. Taylor; Daniel J. Steinberger; Terrence J. Adam

Archive | 1999

System, verfahren und erzeugnis zur erstellung von empfehlungen mit hohem gebrauchswert

Paul Bieganski; Joseph A. Konstan; John T. Riedl

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Joseph A. Konstan

University of Minnesota

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Paul Bieganski

University of Minnesota

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Ed H. Chi

Google

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Jonathan L. Herlocker

Oregon State University

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Al Borchers

University of Minnesota

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Badrul Munir Sarwar

University of Minnesota

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Bradley N. Miller

University of Minnesota

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Elizabeth Shoop

University of Minnesota

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Ernest F. Retzel

University of Minnesota

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J. Ben Schafer

University of Northern Iowa

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