Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms
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Published By Springer Berlin Heidelberg

9783642231650, 9783642231667

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DepMiner: A Method and a System for the Extraction of Significant Dependencies

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_8 ◽

2012 ◽

pp. 209-222

Author(s):

Rosa Meo ◽

Leonardo D’Ambrosi

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Regional Association Rule Mining and Scoping from Spatial Data

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_11 ◽

2012 ◽

pp. 289-313

Author(s):

Wei Ding ◽

Christoph F. Eick

Keyword(s):

Spatial Data ◽

Association Rule ◽

Association Rule Mining ◽

Rule Mining ◽

Regional Association

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Integration of Dataset Scans in Processing Sets of Frequent Itemset Queries

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_9 ◽

2012 ◽

pp. 223-266

Author(s):

Marek Wojciechowski ◽

Maciej Zakrzewicz ◽

Pawel Boinski

Keyword(s):

Frequent Itemset

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Clustering Analysis in Large Graphs with Rich Attributes

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_2 ◽

2012 ◽

pp. 7-27

Author(s):

Yang Zhou ◽

Ling Liu

Keyword(s):

Clustering Analysis ◽

Large Graphs

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Data Mining Techniques in Clustering, Association and Classification

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_1 ◽

2012 ◽

pp. 1-6 ◽

Cited By ~ 3

Author(s):

Dawn E. Holmes ◽

Jeffrey Tweedale ◽

Lakhmi C. Jain

Keyword(s):

Data Mining ◽

Data Mining Techniques

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Randomized Algorithm of Finding the True Number of Clusters Based on Chebychev Polynomial Approximation

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_6 ◽

2012 ◽

pp. 131-155 ◽

Cited By ~ 4

Author(s):

R. Avros ◽

O. Granichin ◽

D. Shalymov ◽

Z. Volkovich ◽

G. -W. Weber

Keyword(s):

Polynomial Approximation ◽

Randomized Algorithm ◽

Number Of Clusters ◽

True Number

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Temporal Data Mining: Similarity-Profiled Association Pattern

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_3 ◽

2012 ◽

pp. 29-47 ◽

Cited By ~ 17

Author(s):

Jin Soung Yoo

Keyword(s):

Data Mining ◽

Temporal Data Mining ◽

Temporal Data ◽

Association Pattern

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Bayesian Networks with Imprecise Probabilities: Theory and Application to Classification

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_4 ◽

2012 ◽

pp. 49-93 ◽

Cited By ~ 15

Author(s):

G. Corani ◽

A. Antonucci ◽

M. Zaffalon

Keyword(s):

Bayesian Networks ◽

Imprecise Probabilities

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Hierarchical Clustering for Finding Symmetries and Other Patterns in Massive, High Dimensional Datasets

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_5 ◽

2012 ◽

pp. 95-130

Author(s):

Fionn Murtagh ◽

Pedro Contreras

Keyword(s):

Hierarchical Clustering ◽

High Dimensional ◽

High Dimensional Datasets

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Text Clustering with Named Entities: A Model, Experimentation and Realization

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms ◽

10.1007/978-3-642-23166-7_10 ◽

2012 ◽

pp. 267-287 ◽

Cited By ~ 6

Author(s):

Tru H. Cao ◽

Thao M. Tang ◽

Cuong K. Chau

Keyword(s):

Text Clustering ◽

Named Entities

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Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent ParadigmsLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

DepMiner: A Method and a System for the Extraction of Significant Dependencies

Regional Association Rule Mining and Scoping from Spatial Data

Integration of Dataset Scans in Processing Sets of Frequent Itemset Queries

Clustering Analysis in Large Graphs with Rich Attributes

Data Mining Techniques in Clustering, Association and Classification

Randomized Algorithm of Finding the True Number of Clusters Based on Chebychev Polynomial Approximation

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

Text Clustering with Named Entities: A Model, Experimentation and Realization

Intelligent Systems Reference Library - Data Mining: Foundations and Intelligent Paradigms
Latest Publications