<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="http://www.bibsonomy.org/tag/icdm"><owl:Ontology rdf:about=""><rdfs:comment>BibSonomy publications for /tag/icdm</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/22c34bb4b49187a6d3e780e78d254ae1f/jaeschke"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/22c34bb4b49187a6d3e780e78d254ae1f/jaeschke"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://dx.doi.org/10.1007/s10115-007-0114-2"/><swrc:date>Fri Jan 18 11:04:39 CET 2008</swrc:date><swrc:address>London</swrc:address><swrc:journal>Knowledge and Information Systems</swrc:journal><swrc:month>Jan</swrc:month><swrc:number>1</swrc:number><swrc:pages>1--37</swrc:pages><swrc:publisher><swrc:Organization swrc:name="Springer"/></swrc:publisher><swrc:title>Top 10 algorithms in data mining</swrc:title><swrc:volume>14</swrc:volume><swrc:year>2008</swrc:year><swrc:keywords>icdm algorithm top ieee mining data </swrc:keywords><swrc:abstract>This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM)
in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms are among the most influential data mining algorithms in the research community.With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current andfurther research on the algorithm. These 10 algorithms cover classification, clustering, statistical learning, associationanalysis, and link mining, which are all among the most important topics in data mining research and development.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="0219-1377" swrc:key="issn"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Xindong Wu"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Vipin Kumar"/></rdf:_2><rdf:_3><swrc:Person swrc:name="J. Ross Quinlan"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Joydeep Ghosh"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Qiang Yang"/></rdf:_5><rdf:_6><swrc:Person swrc:name="Hiroshi Motoda"/></rdf:_6><rdf:_7><swrc:Person swrc:name="Geoffrey McLachlan"/></rdf:_7><rdf:_8><swrc:Person swrc:name="Angus Ng"/></rdf:_8><rdf:_9><swrc:Person swrc:name="Bing Liu"/></rdf:_9><rdf:_10><swrc:Person swrc:name="Philip Yu"/></rdf:_10><rdf:_11><swrc:Person swrc:name="Zhi-Hua Zhou"/></rdf:_11><rdf:_12><swrc:Person swrc:name="Michael Steinbach"/></rdf:_12><rdf:_13><swrc:Person swrc:name="David Hand"/></rdf:_13><rdf:_14><swrc:Person swrc:name="Dan Steinberg"/></rdf:_14></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2f7f99750d4711df9471235fa5848ccdb/zeno"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2f7f99750d4711df9471235fa5848ccdb/zeno"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><owl:sameAs rdf:resource="http://dx.doi.org/10.1109/ICDM.2006.117"/><swrc:date>Sun Jun 10 21:28:26 CEST 2007</swrc:date><swrc:address>Washington, DC, USA</swrc:address><swrc:booktitle>ICDM &#039;06: Proceedings of the Sixth International Conference on Data Mining</swrc:booktitle><swrc:pages>1026--1031</swrc:pages><swrc:publisher><swrc:Organization swrc:name="IEEE Computer Society"/></swrc:publisher><swrc:title>Object Identification with Constraints</swrc:title><swrc:year>2006</swrc:year><swrc:keywords>icdm clustering object-identification constraints 2006 </swrc:keywords><swrc:hasExtraField><swrc:Field swrc:value="0-7695-2701-9" swrc:key="isbn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://dx.doi.org/10.1109/ICDM.2006.117" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Steffen Rendle"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Lars Schmidt-Thieme"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2e387c294129e11f4221514d5fa807e26/nepomuk"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2e387c294129e11f4221514d5fa807e26/nepomuk"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><swrc:date>Thu Jan 11 13:54:35 CET 2007</swrc:date><swrc:address>Hong Kong</swrc:address><swrc:booktitle>Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)</swrc:booktitle><swrc:month>December</swrc:month><swrc:pages>907-911</swrc:pages><swrc:publisher><swrc:Organization swrc:name="IEEE Computer Society"/></swrc:publisher><swrc:title>TRIAS - An Algorithm for Mining Iceberg Tri-Lattices</swrc:title><swrc:year>2006</swrc:year><swrc:keywords>2006 fca wp5 algorithm from:jaeschke icdm triadic myown 12 l3s trias issi_example </swrc:keywords><swrc:hasExtraField><swrc:Field swrc:value="1550-4786" swrc:key="issn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.162" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Robert Jäschke"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Andreas Hotho"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Christoph Schmitz"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Bernhard Ganter"/></rdf:_4><rdf:_5><swrc:Person swrc:name="Gerd Stumme"/></rdf:_5></rdf:Seq></swrc:author></rdf:Description><foaf:Group rdf:about="http://www.bibsonomy.org/tag/icdm"><foaf:name>icdm</foaf:name><description>Community for tag(s) icdm</description></foaf:Group></rdf:RDF>