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Document clustering
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#	Item
31	Module: CLUTO Toolkit Draft: Module Name CLUTO Toolkit 2) Scope The module briefly introduces the basic concepts of Clustering. The primary focus of Add to Reading List Source URL: curric.dlib.vt.edu Language: English - Date: 2011-01-19 20:54:37 Information science Statistics Cluster analysis Data analysis Data mining Geostatistics Bioinformatics Hierarchical clustering Document clustering UPGMA Nearest-neighbor chain algorithm Correlation clustering
32	Case Study 2: Document Retrieval Spectral Clustering Machine Learning/Statistics for Big Data CSE599C1/STAT592, University of Washington Emily Fox Add to Reading List Source URL: courses.cs.washington.edu Language: English - Date: 2013-02-15 02:35:02
33	Case Study 2: Document Retrieval Spectral Clustering Machine Learning/Statistics for Big Data CSE599C1/STAT592, University of Washington Emily Fox Add to Reading List Source URL: courses.cs.washington.edu Language: English - Date: 2013-02-14 03:09:08
34	SERVICE STATEMENT JORDAN BOYD-GRABER 1. Professional Service In addition to standard reviewing of articles, I’ve served as an area chair for machine learning at emnlp 2015, document classification and topic clustering Add to Reading List Source URL: www.cs.colorado.edu Language: English - Date: 2016-06-06 14:00:07
35	A Semi-automatic Method for Efficient Detection of Stories on Social Media Soroush Vosoughi, Deb Roy Massachusetts Institute of Technology Cambridge, MA 02139 , Add to Reading List Source URL: socialmachines.media.mit.edu Language: English - Date: 2016-04-07 02:55:33 Software Computing Information science Cluster analysis Document clustering Twitter Hierarchical clustering Dendrogram Social media
36	Web Search and Information Systems Ricardo Campos 1 1 Centre Add to Reading List Source URL: www.ccc.ipt.pt Language: English - Date: 2013-06-14 21:24:48 Data mining Information science Statistics Information Cluster analysis Hierarchical clustering Bioinformatics Web mining Document clustering
37	CLUSTERING WEB PAGE SEARCH RESULTS: A FULL TEXT BASED APPROACH 1 Ricardo Campos 1, 2, Gaël Dias 1, Célia Nunes 1, Bono Nonchev 1 2 Centre for Human Language Technology and Bioinformatics, University of Beira Interior, Add to Reading List Source URL: www.ccc.ipt.pt Language: English - Date: 2010-05-05 12:02:17 Information science Information retrieval Data mining Natural language processing Document clustering Hierarchical clustering Cluster analysis K-means clustering Cluster hypothesis Search engine indexing Query expansion Full text search
38	Content Extraction Using Diverse Feature Sets Matthew E. Peters Dan Lecocq SEOmoz Add to Reading List Source URL: www2013.wwwconference.org Language: English - Date: 2014-07-21 08:47:02 Computational linguistics Algorithm Mathematical logic Theoretical computer science Data mining Information science Academia Natural language processing Mathematics Document clustering Automatic summarization
39	doi:rsta Add to Reading List Source URL: www.nactem.ac.uk Language: English - Date: 2015-07-16 05:36:33 Information science Information retrieval Natural language processing Document clustering National Centre for Text Mining Search engine indexing Full text search Document classification Text mining Terminology extraction Search engine technology UK Educational Evidence Portal
40	ARTICLE IN PRESS Information Processing and Management xxxxxx–xxx Contents lists available at ScienceDirect Information Processing and Management Add to Reading List Source URL: www.bic.kyoto-u.ac.jp Language: English - Date: 2009-05-20 08:58:44 Statistics Information science Information Cluster analysis Machine learning Natural language processing Document clustering K-means clustering Hierarchical clustering Expectationmaximization algorithm Mixture model Information retrieval

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