£107.98

Springer Mining of Data with Complex Structures: 333 Book

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Description

Master the complexities of advanced data analysis with Mining of Data with Complex Structures. Published by Springer as part of the Studies in Computational Intelligence series, this technical resource provides a deep dive into managing non-linear data formats. It is designed for researchers and professionals needing to understand the nature of sequences, trees, and graphs. This book moves beyond simple datasets to address the specific challenges of complex data architectures. You will find a detailed background on the current state-of-the-art in sequence, tree, and graph mining. By exploring essential aspects such as subtree types, support definitions, and constraints, this text provides the theoretical foundation necessary for high-level computational work. Beyond theory, the text addresses practical implementation. It covers vital considerations for developing mining algorithms, including enumeration strategies and data structures. A key highlight is the detailed explanation of the Tree Model Guided (TMG) approach, providing the mathematical models required to implement effective tree mining solutions in real-world applications.

Key Features

Clarifies the fundamental nature of complex data structures including sequences, trees, and graphs for better analytical accuracy.

Provides a comprehensive background on the current state-of-the-art research in sequence, tree, and graph mining techniques.

Defines essential tree mining parameters such as subtree types, support definitions, and specific constraints.

Outlines practical implementation issues for algorithm development, covering enumeration strategies and necessary data structures.

Details the Tree Model Guided (TMG) approach and provides the mathematical models needed for advanced tree mining.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
25 February 2013
Listed Since
08 February 2013

Barcode

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