Network Science Network Science offers comprehensive insight on
network analysis and network optimization algorithms, with simple
step-by-step guides and examples throughout, and a thorough
introduction and history of network science, explaining the key
concepts and the type of data needed for network analysis, ensuring
a smooth learning experience for readers. It also includes a
detailed introduction to multiple network optimization algorithms,
including linear assignment, network flow and routing problems. The
text is comprised of five chapters, focusing on subgraphs, network
analysis, network optimization, and includes a list of case
studies, those of which include influence factors in
telecommunications, fraud detection in taxpayers, identifying the
viral effect in purchasing, finding optimal routes considering
public transportation systems, among many others. This insightful
book shows how to apply algorithms to solve complex problems in
real-life scenarios and shows the math behind these algorithms,
enabling readers to learn how to develop them and scrutinize the
results. Written by a highly qualified author with significant
experience in the field, Network Science also includes information
on: Sub-networks, covering connected components, bi-connected
components, community detection, k-core decomposition, reach
network, projection, nodes similarity and pattern matching Network
centrality measures, covering degree, influence, clustering
coefficient, closeness, betweenness, eigenvector, PageRank, hub and
authority Network optimization, covering clique, cycle, linear
assignment, minimum-cost network flow, maximum network flow
problem, minimum cut, minimum spanning tree, path, shortest path,
transitive closure, traveling salesman problem, vehicle routing
problem and topological sort With in-depth and authoritative
coverage of the subject and many case studies to convey concepts
clearly, Network Science is a helpful training resource for
professional and industry workers in, telecommunications,
insurance, retail, banking, healthcare, public sector, among
others, plus as a supplementary reading for an introductory Network
Science course for undergraduate students.
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