Topic model kernel classification with probabilistically reduced features Nguyen, Vu, Phung, Dinh and Venkatesh, Svetha 2015, Topic model kernel classification with probabilistically reduced features, Journal of data science, vol. 13, no. 2, pp. 323-340. Attached Files Name Description MIMEType Size Downloads Title Topic model kernel classification with probabilistically reduced features Author(s) Nguyen, Vu Phung, Dinh orcid.org/0000-0002-9977-8247 Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Journal name Journal of data science Volume number 13 Issue number 2 Start page 323 End page 340 Total pages 18 Publisher Department of Statistics, Columbia University Place of publication New York, N.Y. Publication date 2015-04 ISSN 1680-743X 1683-8602 Keyword(s) topic models Bayesian nonparametic support vector machine kernel method classification dimensionality reduction Summary Probabilistic topic models have become a standard in modern machine learning to deal with a wide range of applications. Representing data by dimensional reduction of mixture proportion extracted from topic models is not only richer in semantics interpretation, but could also be informative for classification tasks. In this paper, we describe the Topic Model Kernel (TMK), a topicbased kernel for Support Vector Machine classification on data being processed by probabilistic topic models. The applicability of our proposed kernel is demonstrated in several classification tasks with real world datasets. TMK outperforms existing kernels on the distributional features and give comparative results on nonprobabilistic data types. Language eng Field of Research 080109 Pattern Recognition and Data Mining Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2015, Department of Statistics, Columbia University Persistent URL http://hdl.handle.net/10536/DRO/DU:30076891 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Related Links Link Description Publisher URL Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 26 Aug 2015, 14:51:23 EST Thu, 27 Aug 2015, 05:08:46 EST Thu, 27 Aug 2015, 08:51:58 EST Thu, 27 Aug 2015, 08:58:11 EST Tue, 17 May 2016, 14:47:08 EST Wed, 18 May 2016, 06:21:39 EST Thu, 02 Jun 2016, 16:27:20 EST Thu, 02 Jun 2016, 16:28:01 EST Fri, 07 Oct 2016, 14:15:28 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 480 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Tue, 17 May 2016, 14:47:08 EST

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