Data Mining: Foundations and Intelligent Paradigms Volume 1: Clustering, Association and Classification /
Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 1of this three volume series, we have brought together contributions from some of the most prestigious researchers in the fundamental data mining tasks of clustering, association and classific...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2012.
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| Σειρά: | Intelligent Systems Reference Library,
23 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Introductory Chapter
- Clustering Analysis in Large Graphs with Rich Attributes
- Temporal Data Mining: Similarity-Profiled Association Pattern
- Bayesian Networks with Imprecise Probabilities: Theory and Application to Classification
- Hierarchical Clustering for Finding Symmetries and Other Patterns in Massive, High Dimensional Datasets
- Randomized Algorithm of Finding the True Number of Clusters Based on Chebychev Polynomial Approximation
- Bregman Bubble Clustering: A Robust Framework for Mining Dense Clusters
- DepMiner: A method and a system for the extraction of significant dependencies
- Integration of Dataset Scans in Processing Sets of Frequent Itemset Queries
- Text Clustering with Named Entities: A Model, Experimentation and Realization
- Regional Association Rule Mining and Scoping from Spatial Data
- Learning from Imbalanced Data: Evaluation Matters.
