Advances in Mining Graphs, Trees and Sequences

Name: Advances in Mining Graphs, Trees and Sequences
SKU: 1919616
Price: 264.99 AUD
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Paperback / softback

Series:

Frontiers in Artificial Intelligence and Applications

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Description

Ever since the early days of machine learning and data mining, it has been realized that the traditional attribute-value and item-set representations are too limited for many practical applications in domains such as chemistry, biology, network analysis and text mining. This has triggered a lot of research on mining and learning within alternative and more expressive representation formalisms such as computational logic, relational algebra, graphs, trees and sequences. The motivation for using graphs, trees and sequences. Is that they are 1) more expressive than flat representations, and 2) potentially more efficient than multi-relational learning and mining techniques. At the same time, the data structures of graphs, trees and sequences are among the best understood and most widely applied representations within computer science. Thus these representations offer ideal opportunities for developing interesting contributions in data mining and machine learning that are both theoretically well-founded and widely applicable. The goal of this book is to collect recent outstanding studies on mining and learning within graphs, trees and sequences in studies worldwide.

Release date Australia

June 1st, 2005

Audience

Professional & Vocational

Contributors

Edited by J.N. Kok
Edited by Luc De Raedt
Edited by T. Washio

Illustrations

illustrations

Pages

220

Series

Frontiers in Artificial Intelligence and Applications

Dimensions

189x246x11

ISBN-13

9781586035280

Product ID

1919616

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