La Jolla / Washington / D.C. / Sapporo / San Francisco / Heidelberg / Toronto / Bonn / Chemnitz / /
Company
Lockheed Martin / Fair Isaac Inc. / Air Force Research Laboratory / Reuters / Lewis D. D. / AAAI Press / Sun Microsystems Inc. / /
Country
Germany / Japan / Jordan / United States / / /
Facility
Air Force Research Laboratory / Technical University / University of California / /
IndustryTerm
power law / text mining tasks / closed-form solution / power law pi / /
Organization
Technical University of Denmark / American Society of Information Science / idf / Department of Informatics and Mathematical Modelling / Department of Computer Science and Engineering / University of California / San Diego / Association for Computational Linguistics / /
Person
Charles Elkan / Morgan Kaufmann / David Kauchak / /
Position
author / multinomial model for each class / multinomial model for two standard text mining tasks / vector space model for automatic indexing / /
Product
C-0075 / /
ProvinceOrState
California / /
PublishedMedium
Computational Linguistics / Machine Learning / Communications of the ACM / Journal of Machine Learning Research / /
Modeling Word Burstiness Using the Dirichlet Distribution Rasmus E. Madsen [removed] Department of Informatics and Mathematical Modelling, Technical University of Denmark David Kauchak