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Topic · Data Mining Algorithms and Applications

Most cited papers in Data Mining Algorithms and Applications

Data Mining Algorithms and Applications

What are the most cited papers in Data Mining Algorithms and Applications?

The most cited paper in Data Mining Algorithms and Applications is "An introduction to ROC analysis" (Tom E. Fawcett, 2005), with 22,014 citations. Next come "The Elements of Statistical Learning: Data Mining, Inference, and Prediction" (19,372) and "A density-based algorithm for discovering clusters in large spatial Databases with Noise" (19,125).

Showing 50 of 96 papers. Every paper with more than 1,487 citations is listed.

Most cited papers, sortable by citations and release date
#Paper
1 An introduction to ROC analysis Tom E. Fawcett · Pattern Recognition Letters 22 Dec 2005 22,014
2 The Elements of Statistical Learning: Data Mining, Inference, and Prediction Trevor Hastie, Robert John Tibshirani, Jerome H. Friedman 28 Jul 2013 19,372
3 A density-based algorithm for discovering clusters in large spatial Databases with Noise Martin Ester, Hans‐Peter Kriegel, Jörg Sander et al. 1996 19,125
4 The WEKA data mining software Mark Michael Hall, Eibe Frank, Geoffrey Holmes et al. · ACM SIGKDD Explorations Newsletter Open access 16 Nov 2009 17,902
5 Bagging Predictors Leo Breiman · Machine Learning Open access Aug 1996 17,320
6 jModelTest 2: more models, new heuristics and parallel computing Diego Darriba, Guillermo L. Taboada, Ramón Doallo et al. · Nature Methods Open access 30 Jul 2012 17,284
7 Mining association rules between sets of items in large databases Rakesh Agrawal, Tomasz Imieliński, Arun N. Swami Conference paperOpen access Jun 1993 14,855
8 Induction of decision trees J. R. Quinlan · Machine Learning Open access Mar 1986 12,440
9 A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection Ron Kohavi Open access 1995 10,735
10 A vector space model for automatic indexing Gerard Salton, Anita M.-Y. Wong, Chul‐Su Yang · Communications of the ACM Open access Nov 1975 7,521
11 FCM: The fuzzy c-means clustering algorithm James C. Bezdek, Robert Ehrlich, William E. Full · Computers & Geosciences 1984 6,688
12 The relationship between Precision-Recall and ROC curves Jesse J. Davis, Mark Goadrich Conference paperOpen access 2006 6,494
13 Mining frequent patterns without candidate generation Jiawei Han, Jian Pei, Yiwen Yin · ACM SIGMOD Record 16 May 2000 6,393
14 Business Intelligence and Analytics: From Big Data to Big Impact Hsinchun Chen, Roger H.L. Chiang, Veda C. Storey · MIS Quarterly Dec 2012 6,224
15 The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation Davide Chicco, Giuseppe Jurman · BMC Genomics Open access 2 Jan 2020 6,216
16 Top 10 algorithms in data mining Xindong Wu, Vipin Kumar, J. R. Quinlan et al. · Knowledge and Information Systems 3 Dec 2007 5,723
17 The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets Takaya Saito, Marc Rehmsmeier · PLoS ONE Open access 4 Mar 2015 5,231
18 Mining sequential patterns Ramesh Kumar Agrawal, Ramakrishnan Srikant Conference paper 19 Nov 2002 5,175
19 Data mining Ian H. Witten, Eibe Frank · ACM SIGMOD Record Mar 2002 5,167
20 Random decision forests Tin Kam Ho Conference paper 19 Nov 2002 5,158
21 Bayesian Network Classifiers Nir Friedman, Dan Geiger, Moisés Goldszmidt · Machine Learning Open access Nov 1997 4,769
22 Data mining and knowledge discovery: making sense out of data U.M. Feyyad · IEEE Expert Oct 1996 4,643
23 Empirical Analysis of Predictive Algorithms for Collaborative Filtering John S. Breese, David E. Heckerman, Carl Myers Kadie · arXiv (Cornell University) PreprintOpen access 30 Jan 2013 4,504
24 BPR: Bayesian Personalized Ranking from Implicit Feedback Steffen Rendle, Christoph Freudenthaler, Zeno Gantner et al. · arXiv (Cornell University) PreprintOpen access 9 May 2012 4,399
25 A study of the behavior of several methods for balancing machine learning training data Gustavo E. A. P. A. Batista, Ronaldo Cristiano Prati, Maria Carolina Monard · ACM SIGKDD Explorations Newsletter Jun 2004 4,251
26 Probabilistic Latent Semantic Indexing Thomas Frank Hofmann · ACM SIGIR Forum 2 Aug 2017 4,050
27 GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists Eran Eden, Roy Navon, Israel Steinfeld et al. · BMC Bioinformatics Open access 3 Feb 2009 3,726
28 A Bayesian Method for the Induction of Probabilistic Networks from Data Gregory F. Cooper, Edward H. Herskovits · Machine Learning Open access Oct 1992 3,533
29 Theoretical and Empirical Analysis of ReliefF and RReliefF Marko Robnik‐Šikonja, Igor Kononenko · Machine Learning Open access 23 Sep 2003 3,031
30 A Practical Approach to Feature Selection Kenji Kira, Larry A. Rendell · Elsevier eBooks Book chapter 1992 3,002
31 Gene selection and classification of microarray data using random forest Ramón Díaz‐Uriarte, Sara Álvarez de Andrés · BMC Bioinformatics Open access 6 Jan 2006 2,990
32 Estimating attributes: Analysis and extensions of RELIEF Igor Kononenko · Lecture notes in computer science Conference paper 1994 2,986
33 An Introduction to Statistical Learning: with Applications in R Gareth M. James, Daniela Witten, Trevor Hastie et al. Open access 2018 2,986
34 Consistent Partial Least Squares Path Modeling1 Theo K. Dijkstra, Jörg Henseler · MIS Quarterly Open access Jun 2015 2,843
35 An Algorithm for Finding Best Matches in Logarithmic Expected Time Jerome H. Friedman, Jon Louis Bentley, Raphael A. Finkel · ACM Transactions on Mathematical Software Sep 1977 2,828
36 DBSCAN Revisited, Revisited Erich Schubert, Jörg Sander, Martin Ester et al. · ACM Transactions on Database Systems 31 Jul 2017 2,772
37 An empirical comparison of supervised learning algorithms Rich Caruana, Alexandru Niculescu-Mizil Conference paper 2006 2,746
38 Mining sequential patterns: Generalizations and performance improvements Ramakrishnan Srikant, Rakesh Agrawal · Lecture notes in computer science Conference paper 1996 2,716
39 Toward integrating feature selection algorithms for classification and clustering Huan Liu, Lei Yu · IEEE Transactions on Knowledge and Data Engineering 7 Mar 2005 2,712
40 Ensemble-based classifiers Lior Rokach · Artificial Intelligence Review Open access 18 Nov 2009 2,694
41 On Clustering Validation Techniques Maria Halkidi, Yannis Batistakis, Michalis Vazirgiannis · Journal of Intelligent Information Systems Dec 2001 2,679
42 An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Carolin Strobl, James D. Malley, Gerhard Tutz · Psychological Methods Open access Dec 2009 2,645
43 Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach Jiawei Han, Jian Pei, Yiwen Yin et al. · Data Mining and Knowledge Discovery 25 Nov 2003 2,636
44 Feature selection for classification Manoranjan Dash, Hua Liu · Intelligent Data Analysis 1997 2,613
45 Simplifying decision trees J. R. Quinlan · International Journal of Man-Machine Studies Open access Sep 1987 2,551
46 Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values Zhexue Huang · Data Mining and Knowledge Discovery Sep 1998 2,525
47 Data mining with big data Xindong Wu, Xingquan Zhu, Gongqing Wu et al. · IEEE Transactions on Knowledge and Data Engineering 26 Jun 2013 2,429
48 Automatic subspace clustering of high dimensional data for data mining applications Rakesh Agrawal, Johannes E. Gehrke, Dimitrios Gunopulos et al. Conference paper Jun 1998 2,402
49 Irrelevant Features and the Subset Selection Problem George H. John, Ron Kohavi, Karl Pfleger · Elsevier eBooks Book chapter 1994 2,393
50 Accelerating t-SNE using tree-based algorithms Laurens van der Maaten 2014 2,392

Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.