| # | Title | Journal | Year | Citations |
|---|
| 1 | A Tutorial on Support Vector Machines for Pattern Recognition | Data Mining and Knowledge Discovery | 1998 | 12,673 |
| 2 | Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach | Data Mining and Knowledge Discovery | 2004 | 2,034 |
| 3 | Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values | Data Mining and Knowledge Discovery | 1998 | 1,773 |
| 4 | Deep learning for time series classification: a review | Data Mining and Knowledge Discovery | 2019 | 1,656 |
| 5 | Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals | Data Mining and Knowledge Discovery | 1997 | 1,218 |
| 6 | Experiencing SAX: a novel symbolic representation of time series | Data Mining and Knowledge Discovery | 2007 | 1,190 |
| 7 | Frequent pattern mining: current status and future directions | Data Mining and Knowledge Discovery | 2007 | 1,109 |
| 8 | Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications | Data Mining and Knowledge Discovery | 1998 | 1,059 |
| 9 | E-Commerce Recommendation Applications | Data Mining and Knowledge Discovery | 2001 | 1,056 |
| 10 | Discovery of Frequent Episodes in Event Sequences | Data Mining and Knowledge Discovery | 1997 | 974 |
| 11 | Bursty and Hierarchical Structure in Streams | Data Mining and Knowledge Discovery | 2003 | 898 |
| 12 | Graph based anomaly detection and description: a survey | Data Mining and Knowledge Discovery | 2015 | 897 |
| 13 | The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances | Data Mining and Knowledge Discovery | 2017 | 838 |
| 14 | Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey | Data Mining and Knowledge Discovery | 1998 | 751 |
| 15 | On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality | Data Mining and Knowledge Discovery | 1997 | 729 |
| 16 | Discretization: An Enabling Technique | Data Mining and Knowledge Discovery | 2002 | 729 |
| 17 | Levelwise Search and Borders of Theories in Knowledge Discovery | Data Mining and Knowledge Discovery | 1997 | 706 |
| 18 | A survey of hierarchical classification across different application domains | Data Mining and Knowledge Discovery | 2011 | 693 |
| 19 | On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach | Data Mining and Knowledge Discovery | 1997 | 653 |
| 20 | Adaptive Fraud Detection | Data Mining and Knowledge Discovery | 1997 | 649 |
| 21 | On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration | Data Mining and Knowledge Discovery | 2003 | 649 |
| 22 | BIRCH: A New Data Clustering Algorithm and Its Applications | Data Mining and Knowledge Discovery | 1997 | 643 |
| 23 | Experimental comparison of representation methods and distance measures for time series data | Data Mining and Knowledge Discovery | 2013 | 612 |
| 24 | Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem | Data Mining and Knowledge Discovery | 1998 | 582 |
| 25 | InceptionTime: Finding AlexNet for time series classification | Data Mining and Knowledge Discovery | 2020 | 542 |
| 26 | Community detection in Social Media | Data Mining and Knowledge Discovery | 2012 | 509 |
| 27 | Bayesian Networks for Data Mining | Data Mining and Knowledge Discovery | 1997 | 489 |
| 28 | Controlled experiments on the web: survey and practical guide | Data Mining and Knowledge Discovery | 2009 | 486 |
| 29 | Hierarchical Clustering Algorithms for Document Datasets | Data Mining and Knowledge Discovery | 2005 | 452 |
| 30 | Three naive Bayes approaches for discrimination-free classification | Data Mining and Knowledge Discovery | 2010 | 445 |
| 31 | On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study | Data Mining and Knowledge Discovery | 2016 | 445 |
| 32 | Training and assessing classification rules with imbalanced data | Data Mining and Knowledge Discovery | 2014 | 444 |
| 33 | Advances in Instance Selection for Instance-Based Learning Algorithms | Data Mining and Knowledge Discovery | 2002 | 435 |
| 34 | Characteristic-Based Clustering for Time Series Data | Data Mining and Knowledge Discovery | 2006 | 435 |
| 35 | Computing LTS Regression for Large Data Sets | Data Mining and Knowledge Discovery | 2006 | 415 |
| 36 | Genetic process mining: an experimental evaluation | Data Mining and Knowledge Discovery | 2007 | 372 |
| 37 | Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation | Data Mining and Knowledge Discovery | 2005 | 370 |
| 38 | Classification of time series by shapelet transformation | Data Mining and Knowledge Discovery | 2014 | 368 |
| 39 | ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels | Data Mining and Knowledge Discovery | 2020 | 359 |
| 40 | FURIA: an algorithm for unordered fuzzy rule induction | Data Mining and Knowledge Discovery | 2009 | 351 |
| 41 | Time series classification with ensembles of elastic distance measures | Data Mining and Knowledge Discovery | 2015 | 349 |
| 42 | Community discovery using nonnegative matrix factorization | Data Mining and Knowledge Discovery | 2011 | 348 |
| 43 | The BOSS is concerned with time series classification in the presence of noise | Data Mining and Knowledge Discovery | 2015 | 340 |
| 44 | On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms | Data Mining and Knowledge Discovery | 2004 | 323 |
| 45 | Survey on mining subjective data on the web | Data Mining and Knowledge Discovery | 2012 | 307 |
| 46 | Mining Non-Redundant Association Rules | Data Mining and Knowledge Discovery | 2004 | 304 |
| 47 | Efficient Adaptive-Support Association Rule Mining for Recommender Systems | Data Mining and Knowledge Discovery | 2002 | 301 |
| 48 | (null) | Data Mining and Knowledge Discovery | 2001 | 294 |
| 49 | Finding Frequent Patterns in a Large Sparse Graph* | Data Mining and Knowledge Discovery | 2005 | 285 |
| 50 | Characterizing concept drift | Data Mining and Knowledge Discovery | 2016 | 285 |
