000			04308nam a22005055i 4500
001			978-0-8176-4789-6
003			DE-He213
005			20251006084439.0
007			cr nn 008mamaa
008			101029s2011 xxu| s |||| 0|eng d
020			_a9780817647896
020			_a99780817647896
024	7		_a10.1007/978-0-8176-4789-6 _2doi
082	0	4	_a519 _223
100	1		_aDehmer, Matthias. _eeditor.
245	1	0	_aStructural Analysis of Complex Networks _h[electronic resource] / _cedited by Matthias Dehmer.
264		1	_aBoston : _bBirkhäuser Boston, _c2011.
300			_aXIV, 478p. 85 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aPreface -- A Brief Introduction to Complex Networks and Their Analysis -- Partitions of Graphs -- Distance in Graphs -- Domination in Graphs -- Spectrum and Entropy for Infinite Directed Graphs -- Application of Infinite Labeled Graphs to Symbolic Dynamical Systems -- Decompositions and Factorizations of Complete Graphs -- Geodetic Sets in Graphs -- Graph Polynomials and Their Applications I: The Tutte Polynomial -- Graph Polynomials and Their Applications II: Interrelations and Interpretations -- Reconstruction Problems for Graphs, Krawtchouk Polynomials, and Diophantine Equations -- Subgraphs as a Measure of Similarity -- A Chromatic Metric on Graphs -- Some Applications of Eigenvalues of Graphs -- Minimum Spanning Markovian Trees: Introducing Context-Sensitivity Into the Generation of Spanning Trees -- Link-Based Network Mining -- Graph Representations and Algorithms in Computational Biology of RNA Secondary Structure -- Inference of Protein Function from the Structure of Interaction Networks -- Applications of Perfect Matchings in Chemistry -- Index.
520			_aBecause of the increasing complexity and growth of real-world networks, their analysis by using classical graph-theoretic methods is oftentimes a difficult procedure. As a result, there is a strong need to combine graph-theoretic methods with mathematical techniques from other scientific disciplines, such as machine learning and information theory, in order to analyze complex networks more adequately. Filling a gap in literature, this self-contained book presents theoretical and application-oriented results to structurally explore complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Special emphasis is given to methods related to the following areas: * Applications to biology, chemistry, linguistics, and data analysis * Graph colorings * Graph polynomials * Information measures for graphs * Metrical properties of graphs * Partitions and decompositions * Quantitative graph measures Structural Analysis of Complex Networks is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. The book may be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.
650		0	_aMATHEMATICS.
650		0	_aCOMPUTER COMMUNICATION NETWORKS.
650		0	_aCOMPUTATIONAL COMPLEXITY.
650		0	_aDATA MINING.
650		0	_aBIOINFORMATICS.
650		0	_aCOMBINATORICS.
650	1	4	_aMATHEMATICS.
650	2	4	_aAPPLICATIONS OF MATHEMATICS.
650	2	4	_aDISCRETE MATHEMATICS IN COMPUTER SCIENCE.
650	2	4	_aCOMBINATORICS.
650	2	4	_aCOMPUTER COMMUNICATION NETWORKS.
650	2	4	_aCOMPUTATIONAL BIOLOGY/BIOINFORMATICS.
650	2	4	_aDATA MINING AND KNOWLEDGE DISCOVERY.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780817647889
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-8176-4789-6 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c59788 _d59788