Data Mining and Knowledge Discovery Handbook, 2nd ed

By Oded Z. Maimon, Lior Rokach. Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

311 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/dd8a73e78c1a351b5537a721e1a6356a7ef4ed90

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1. José Antonio Lozano
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4. Angel Conde

Citations in the corpus

• A Review on Outlier/Anomaly Detection in Time Series Data (2020, methodology): “Given that the well-known k-means clustering algorithm is not useful for unsynchronized variables because it uses the Euclidean distance, Rebbapragada et al. [2009] propose using Phased k-means in unsynchronized periodic multivariate time series.”
• Human-Computer Interaction and Knowledge Discovery (HCI-KDD): What Is the Benefit of Bringing Those Two Fields to Work Together? (2013, unknown): “Maimon & Rokach (2010) [46] define Knowledge Discovery in Databases (KDD) as an automatic, exploratory analysis and modeling of large data repositories and the organized process of identifying valid, novel, useful and understandable patterns from large and complex data sets.”