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Mining of Data with Complex Structures by Hadzic, Fedja;Tan, Henry;Dillon, Tharam S is a nonfiction available to read on EtoBox.

What is Mining of Data with Complex Structures about?

Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG

Who reads Mining of Data with Complex Structures?

Author

Hadzic, Fedja;Tan, Henry;Dillon, Tharam S

Publisher

Springer-Verlag Berlin Heidelberg

Published

2010

Language

EN

ISBN

9781280010033

Category

nonfiction

Subjects

Mathematics, Engineering, Science