Data clustering using side information dependent Chinese restaurant processes Li, Cheng, Rana, Santu, Phung,D and Venkatesh,S 2016, Data clustering using side information dependent Chinese restaurant processes, Knowledge and information systems, vol. 47, no. 2, pp. 463-488, doi: 10.1007/s10115-015-0834-7. Attached Files Name Description MIMEType Size Downloads Title Data clustering using side information dependent Chinese restaurant processes Author(s) Li, Cheng Rana, Santu orcid.org/0000-0003-2247-850X Phung,D orcid.org/0000-0002-9977-8247 Venkatesh,S orcid.org/0000-0001-8675-6631 Journal name Knowledge and information systems Volume number 47 Issue number 2 Start page 463 End page 488 Total pages 26 Publisher Springer Place of publication Berlin, Germany Publication date 2016-05 ISSN 0219-1377 0219-3116 Keyword(s) Side information Similarity Data clustering Bayesian nonparametric models Summary Side information, or auxiliary information associated with documents or image content, provides hints for clustering. We propose a new model, side information dependent Chinese restaurant process, which exploits side information in a Bayesian nonparametric model to improve data clustering. We introduce side information into the framework of distance dependent Chinese restaurant process using a robust decay function to handle noisy side information. The threshold parameter of the decay function is updated automatically in the Gibbs sampling process. A fast inference algorithm is proposed. We evaluate our approach on four datasets: Cora, 20 Newsgroups, NUS-WIDE and one medical dataset. Types of side information explored in this paper include citations, authors, tags, keywords and auxiliary clinical information. The comparison with the state-of-the-art approaches based on standard performance measures (NMI, F1) clearly shows the superiority of our approach. Language eng DOI 10.1007/s10115-015-0834-7 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 ©2016, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30076873 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Related Links Link Description Connect to published version 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, 14:46:23 EST Thu, 27 Aug 2015, 05:07:55 EST Thu, 27 Aug 2015, 08:51:27 EST Thu, 27 Aug 2015, 08:57:41 EST Mon, 07 Mar 2016, 14:59:31 EST Tue, 08 Mar 2016, 05:06:52 EST Mon, 11 Apr 2016, 12:19:24 EST Mon, 11 Apr 2016, 12:22:36 EST Wed, 13 Apr 2016, 13:52:16 EST Mon, 18 Jul 2016, 15:41:34 EST Fri, 16 Jun 2017, 12:22:25 EST Filtered Full Citation counts:   Cited 3 times in TR Web of Science Cited 6 times in Scopus Search Google Scholar Access Statistics: 685 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Mon, 07 Mar 2016, 14:59:31 EST

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