Data Mining: Concepts, Models, Methods, and Algorithms

By D. Edwards. 2003

1,508 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems

View Paper: https://www.semanticscholar.org/paper/c60c59b1873a6635594ed7cb7eab9f90727f326c

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Citations in the corpus

Will Artificial Intelligence Take Over Humanresources Recruitment And Selection (2019, background): “ANN relies on machine learning and it aims to capture the parallel and distributed structure of the human nervous system as an attempt to simulate human learning capability (Lucci & Kopec, 2016).”
Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis (2009, background): “A major problem inherit with quadratic TFDs is cross-terms (interference), which is the result of the quadratic nature of transformation.”
Data Mining techniques for the detection of fraudulent financial statements (2007, background): “DM is most useful in an exploratory analysis scenario in which there are no predetermined notions about what will constitute an ''interesting'' outcome (Kantardzic, 2002).”
Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier (2020, result): “This result accords with the conclusion of Kantardzic [132] that the Bagging Tree–Cubic KNN model performs better than rival models (Figure 9).”
The seven deadly sins of comparative analysis (2009, background): “…when large amounts of data have been collected with few a priori expectations of how different variables will relate to each other, statistical testing may not be appropriate and alternative techniques such as data mining should be considered (see Kantarszic, 2002 for an overview of techniques).”
Multivariate Time Series Imputation with Generative Adversarial Networks (2018, background): “Simple imputation algorithms impute the missing values with some statistical attributes, such as replace missing value with mean value [27], impute with median value [1], impute with most common value [12] and complete the dataset with last observed valid value [2].”
Measuring firm performance using financial ratios: A decision tree approach (2013, background): “The first principal component has the highest degree of variance; the second principal component has the second highest degree of variance, and so forth (Kantardzic, 2003).”
Isolated items discarding strategy for discovering high utility itemsets (2008, background): “The development of data mining techniques has focused on eﬃciently discovering hidden information from large databases that is useful for corporate decision-makers [20].”
A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques (2017, background): “There has been a tremendous quantities of research for data mining and statistical learning [1, 62, 78, 137].”