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Mining of Data with Complex Structures by Fedja Hadzic; Henry Tan; Tharam S. Dillon 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 fram

Who reads Mining of Data with Complex Structures?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Fedja Hadzic; Henry Tan; Tharam S. Dillon
Publisher
Springer-Verlag Berlin Heidelberg
Published
2011
Language
EN
ISBN
9783642267031
Category
nonfiction
Subjects
Engineering, Mathematics, Computer Science

Other editions & translations

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