7.7(top 2%)
impact factor
422(top 50%)
papers
19.5K(top 10%)
citations
64(top 10%)
h-index
8.1(top 2%)
impact factor
626
all documents
21.2K
doc citations
130(top 10%)
g-index
Top Articles
| # | Title | Journal | Year | Citations |
|---|---|---|---|---|
| 1 | Classification and regression trees | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 1,363 |
| 2 | Ensemble learning: A survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 1,286 |
| 3 | Deep learning for sentiment analysis: A survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 898 |
| 4 | Algorithms for hierarchical clustering: an overview | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2012 | 787 |
| 5 | Hyperparameters and tuning strategies for random forest | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2019 | 651 |
| 6 | Causability and explainability of artificial intelligence in medicine | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2019 | 647 |
| 7 | Density‐based clustering | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 576 |
| 8 | Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2012 | 516 |
| 9 | Data mining in education | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2013 | 515 |
| 10 | Replaying history on process models for conformance checking and performance analysis | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2012 | 457 |
| 11 | Robust statistics for outlier detection | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 434 |
| 12 | A survey on multi‐output regression | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2015 | 367 |
| 13 | Educational data mining and learning analytics: An updated survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2020 | 332 |
| 14 | Bias in data‐driven artificial intelligence systems—An introductory survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2020 | 265 |
| 15 | Deep learning for remote sensing image classification: A survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 222 |
| 16 | Explainable artificial intelligence: an analytical review | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2021 | 198 |
| 17 | Frequent item set mining | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2012 | 195 |
| 18 | Recent trends in machine learning for human activity recognition—A survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 186 |
| 19 | Community detection in social networks | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2016 | 183 |
| 20 | Interpretability of machine learning‐based prediction models in healthcare | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2020 | 178 |
| 21 | Big Data with Cloud Computing: an insight on the computing environment, | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2014 | 175 |
| 22 | Randomness in neural networks: an overview | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2017 | 175 |
| 23 | Applications of tensor (multiway array) factorizations and decompositions in data mining | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 167 |
| 24 | A survey of itemset mining | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2017 | 163 |
| 25 | Algorithms for hierarchical clustering: an overview, | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2017 | 159 |
| 26 | Multivariate random forests | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 153 |
| 27 | Subgroup discovery | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2015 | 150 |
| 28 | Cluster ensembles | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 149 |
| 29 | Mining data with random forests: current options for real‐world applications | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2014 | 140 |
| 30 | Frequent itemset mining: A 25 years review | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2019 | 138 |
| 31 | Support vector machines in engineering: an overview | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2014 | 137 |
| 32 | Multi‐label learning: a review of the state of the art and ongoing research | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2014 | 130 |
| 33 | Social network analysis: An overview | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 127 |
| 34 | Identifying patterns in spatial information: A survey of methods | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 126 |
| 35 | Anomaly detection by robust statistics | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 122 |
| 36 | A survey on educational process mining | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 116 |
| 37 | A historical perspective of explainable Artificial Intelligence | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2021 | 116 |
| 38 | Deep learning for sentiment analysis: successful approaches and future challenges | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2015 | 115 |
| 39 | Credibility in social media: opinions, news, and health information—a survey | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2017 | 115 |
| 40 | Enterprise data breach: causes, challenges, prevention, and future directions | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2017 | 114 |
| 41 | A review of automatic differentiation and its efficient implementation | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2019 | 113 |
| 42 | On the number of components in a Gaussian mixture model | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2014 | 110 |
| 43 | A survey of incremental high‐utility itemset mining | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 110 |
| 44 | There and back again: Outlier detection between statistical reasoning and data mining algorithms | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 108 |
| 45 | Performance evaluation in non‐intrusive load monitoring: Datasets, metrics, and tools—A review | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2018 | 107 |
| 46 | Data discretization: taxonomy and big data challenge | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2016 | 105 |
| 47 | The use of classification trees for bioinformatics | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 103 |
| 48 | Data mining tools | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2011 | 100 |
| 49 | Clustering high dimensional data | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2012 | 99 |
| 50 | Generating ensembles of heterogeneous classifiers using Stacked Generalization | Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery | 2015 | 98 |