Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science
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Published By Springer Berlin Heidelberg

9783540425342, 9783540447948

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Using Grammatical Inference to Automate Information Extraction from the Web

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_18 ◽

2001 ◽

pp. 216-227 ◽

Cited By ~ 13

Author(s):

Theodore W. Hong ◽

Keith L. Clark

Keyword(s):

Information Extraction ◽

Grammatical Inference ◽

Automate Information ◽

The Web

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Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_15 ◽

2001 ◽

pp. 180-191 ◽

Cited By ~ 9

Author(s):

Melanie Hilario ◽

Alexandros Kalousis

Keyword(s):

Model Selection ◽

Meta Data ◽

Case Based

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Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_45 ◽

2001 ◽

pp. 507-507

Author(s):

Stefan Wrobel

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A General Measure of Rule Interestingness

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_21 ◽

2001 ◽

pp. 253-265 ◽

Cited By ~ 19

Author(s):

Szymon Jaroszewicz ◽

Dan A. Simovici

Keyword(s):

General Measure ◽

Rule Interestingness

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Support Vectors for Reinforcement Learning

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_41 ◽

2001 ◽

pp. 492-492

Author(s):

Thomas G. Dietterich ◽

Xin Wang

Keyword(s):

Reinforcement Learning ◽

Support Vectors

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Biological Sequence Data Mining

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_19 ◽

2001 ◽

pp. 228-240 ◽

Cited By ~ 1

Author(s):

Yuh-Jyh Hu

Keyword(s):

Data Mining ◽

Sequence Data ◽

Biological Sequence

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Comparison of Three Objective Functions for Conceptual Clustering

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_33 ◽

2001 ◽

pp. 399-410 ◽

Cited By ~ 6

Author(s):

Céline Robardet ◽

Fabien Feschet

Keyword(s):

Objective Functions ◽

Conceptual Clustering

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Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_37 ◽

2001 ◽

pp. 448-459 ◽

Cited By ~ 3

Author(s):

Shusaku Tsumoto

Keyword(s):

Time Series ◽

Moving Average ◽

Rule Induction ◽

Multiscale Matching

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A Study on the Hierarchical Data Clustering Algorithm Based on Gravity Theory

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_29 ◽

2001 ◽

pp. 350-361 ◽

Cited By ~ 11

Author(s):

Yen-Jen Oyang ◽

Chien-Yu Chen ◽

Tsui-Wei Yang

Keyword(s):

Data Clustering ◽

Clustering Algorithm ◽

Gravity Theory ◽

Hierarchical Data

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A Data Set Oriented Approach for Clustering Algorithm Selection

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science ◽

10.1007/3-540-44794-6_14 ◽

2001 ◽

pp. 165-179 ◽

Cited By ~ 5

Author(s):

Maria Halkich ◽

Michalis Vazirgiannis

Keyword(s):

Clustering Algorithm ◽

Algorithm Selection ◽

Data Set ◽

Oriented Approach

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Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Using Grammatical Inference to Automate Information Extraction from the Web

Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection

Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery

A General Measure of Rule Interestingness

Support Vectors for Reinforcement Learning

Biological Sequence Data Mining

Comparison of Three Objective Functions for Conceptual Clustering

Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction

A Study on the Hierarchical Data Clustering Algorithm Based on Gravity Theory

A Data Set Oriented Approach for Clustering Algorithm Selection

Principles of Data Mining and Knowledge Discovery - Lecture Notes in Computer Science
Latest Publications