Narrow your search

Library

AP (1)

KBC (1)

KDG (1)

KU Leuven (1)

Odisee (1)

Thomas More Kempen (1)

Thomas More Mechelen (1)

UCLL (1)

UGent (1)

ULB (1)

More...

Resource type

book (1)

digital (1)


Language

English (2)


Year
From To Submit

2017 (2)

Listing 1 - 2 of 2
Sort by

Book
Redescription Mining
Authors: ---
ISBN: 331972889X 3319728881 Year: 2017 Publisher: Cham : Springer International Publishing : Imprint: Springer,

Loading...
Export citation

Choose an application

Bookmark

Abstract

This book provides a gentle introduction to redescription mining, a versatile data mining tool that is useful to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. It is intended for readers who are familiar with basic data analysis techniques such as clustering, frequent itemset mining, and classification. Redescription mining is defined in a general way, making it applicable to different types of data. The general framework is made more concrete through many practical examples that show the versatility of redescription mining. The book also introduces the main algorithmic ideas for mining redescriptions, together with applications from various domains. The final part of the book contains variations and extensions of the basic redescription mining problem, and discusses some future directions and open questions. .


Digital
Redescription Mining
Authors: ---
ISBN: 9783319728896 Year: 2017 Publisher: Cham Springer International Publishing

Loading...
Export citation

Choose an application

Bookmark

Abstract

This book provides a gentle introduction to redescription mining, a versatile data mining tool that is useful to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. It is intended for readers who are familiar with basic data analysis techniques such as clustering, frequent itemset mining, and classification. Redescription mining is defined in a general way, making it applicable to different types of data. The general framework is made more concrete through many practical examples that show the versatility of redescription mining. The book also introduces the main algorithmic ideas for mining redescriptions, together with applications from various domains. The final part of the book contains variations and extensions of the basic redescription mining problem, and discusses some future directions and open questions. .

Listing 1 - 2 of 2
Sort by