Lecture Notes in Computer Science - Mining Complex Data
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Published By Springer Berlin Heidelberg

9783540684152, 9783540684169
Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Feature Selection: Near Set Approach

2008 ◽  
pp. 57-71 ◽  
Author(s):  
James F. Peters ◽  
Sheela Ramanna
Keyword(s):  
Feature Selection

Conceptual Clustering Applied to Ontologies

2008 ◽  
pp. 42-56 ◽  
Author(s):  
Floriana Esposito ◽  
Nicola Fanizzi ◽  
Claudia d’Amato
Keyword(s):  
Conceptual Clustering

POM Centric Multi-aspect Data Analysis for Investigating Human Problem Solving Function

2008 ◽  
pp. 252-264 ◽  
Author(s):  
Shinichi Motomura ◽  
Akinori Hara ◽  
Ning Zhong ◽  
Shengfu Lu
Keyword(s):  
Data Analysis ◽  
Problem Solving ◽  
Human Problem

Data Mining of Multi-categorized Data

2008 ◽  
pp. 182-195 ◽  
Author(s):  
Akinori Abe ◽  
Norihiro Hagita ◽  
Michiko Furutani ◽  
Yoshiyuki Furutani ◽  
Rumiko Matsuoka
Keyword(s):  
Data Mining

Ordinal Classification with Decision Rules

2008 ◽  
pp. 169-181 ◽  
Author(s):  
Krzysztof Dembczyński ◽  
Wojciech Kotłowski ◽  
Roman Słowiński
Keyword(s):  
Decision Rules ◽  
Ordinal Classification

Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data

2008 ◽  
pp. 238-251 ◽  
Author(s):  
Dympna O’Sullivan ◽  
William Elazmeh ◽  
Szymon Wilk ◽  
Ken Farion ◽  
Stan Matwin ◽  
...  
Keyword(s):  
Decision Tree ◽  
Clinical Data ◽  
Decision Tree Classification

scholarly journals Learning to Order: A Relational Approach

2008 ◽  
pp. 209-223 ◽  
Author(s):  
Donato Malerba ◽  
Michelangelo Ceci
Keyword(s):  
Relational Approach

Improving Boosting by Exploiting Former Assumptions

2008 ◽  
pp. 131-142
Author(s):  
Emna Bahri ◽  
Nicolas Nicoloyannis ◽  
Mondher Maddouri

Contextual Adaptive Clustering of Web and Text Documents with Personalization

2008 ◽  
pp. 116-130
Author(s):  
Krzysztof Ciesielski ◽  
Mieczysław A. Kłopotek ◽  
Sławomir T. Wierzchoń
Keyword(s):  
Text Documents ◽  
Adaptive Clustering
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