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Association rule learning
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251	Abstract : Scene mining is a subset of image mining in which scenes are classified to a distinct set of classes based on analysis of their content. In other word in scene mining, a label is given to visual content of sce Add to Reading List Source URL: www.science-of-medicine.netne.net Language: English - Date: 2013-02-01 20:19:58 Computer vision Science Data analysis Machine learning Natural language processing Feature extraction Cluster analysis Mining Association rule learning Statistics Data mining Artificial intelligence
252	Introduction to arules – A computational environment for mining association rules and frequent item sets Michael Hahsler Bettina Gru Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-06-17 04:54:36 Data Association rule learning Apriori algorithm Sequence mining Data mining Data management Information
253	Paper number 261 Dynamic Data Mining: Exploring Large Rule Spaces by Sampling Sergey Brin and Lawrence Page Department of Computer Science Add to Reading List Source URL: ilpubs.stanford.edu Language: English - Date: 2008-09-16 20:07:12 Information Hypergraph Dice Data Apriori algorithm Data mining Association rule learning Data management
254	RMonto: Ontological Extension to RapidMiner Jedrzej Potoniec, Agnieszka Lawrynowicz Institute of Computing Science, Pozna´ n University of Technology, Pozna´ n, Poland, Add to Reading List Source URL: iswc2011.semanticweb.org Language: English - Date: 2011-09-19 14:58:11 Knowledge representation Web services Data mining Semantic Web Data analysis RapidMiner SPARQL Association rule learning Semantic reasoner Science Statistics Computing
255	20 Years of Pattern Mining: a Bibliometric Survey Arnaud Giacometti, Dominique H. Li, Patrick Marcel, Arnaud Soulet Universite´ Franc¸ois-Rabelais de Tours, LI EA 6300 Add to Reading List Source URL: www.sigkdd.org Language: English - Date: 2014-02-06 17:59:06 Information science SIGKDD Association rule learning Machine learning Knowledge discovery ECML PKDD Web mining Structure mining Data Data mining Statistics Computational statistics
256	Mining Non-Derivable Association Rules Bart Goethals∗ Juho Muhonen Add to Reading List Source URL: www.cs.helsinki.fi Language: English - Date: 2005-03-01 07:29:35 Mathematics Association rule learning Data management Support Information theory Lift Confidence interval Supremum Entropy Statistics Mathematical analysis Data mining
257	Visualisation of Associations Between Nucleotides in SNP Neighbourhoods Kimmo Kulovesi∗,† , Juho Muhonen∗ , Ilkka Lappalainen‡ , Pentti T. Riikonen§ , Add to Reading List Source URL: www.cs.helsinki.fi Language: English - Date: 2006-06-30 04:01:50 Population genetics DNA Biological databases Genetic genealogy Single-nucleotide polymorphism DbSNP International HapMap Project Association rule learning Human genome Genetics Biology Bioinformatics
258	Closed Non-Derivable Itemsets Juho Muhonen and Hannu Toivonen? Helsinki Institute for Information Technology Add to Reading List Source URL: www.cs.helsinki.fi Language: English - Date: 2006-06-30 03:57:55 Mathematics Mereology Closure Support Information Logic Data mining Association rule learning Data management
259	Clustering and Prediction of Mobile User Routes from Cellular Data Kari Laasonen Add to Reading List Source URL: www.cs.helsinki.fi Language: English - Date: 2005-08-22 06:54:20 Algorithm Association rule learning Mathematics Technology Information technology management Data mining PAQ Cellular network
260	Active learning selection strategies for information extraction Content Areas: Information Extraction, Active Learning 1 Introduction Dual First learn a set of rules to extract instances of some Add to Reading List Source URL: www.aidanf.net Language: English - Date: 2012-10-19 19:38:35 Natural language processing Applied mathematics Computational linguistics Artificial intelligence Data mining Information extraction Algorithm Association rule learning Computational learning theory Theoretical computer science Science Machine learning

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