Posted by **AvaxGenius** at June 24, 2017

English | PDF | 2017 | 278 Pages | ISBN : 3319568280 | 6.84 MB

This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks.

Posted by **AvaxGenius** at May 25, 2017

English | PDF | 2017 | 233 Pages | ISBN : 3319562118 | 6.5 MB

This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation.

Posted by **hill0** at April 30, 2017

English | 14 May 2017 | ISBN: 331953419X | 255 Pages | PDF | 7.45 MB

The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory,

Posted by **nebulae** at April 11, 2017

English | 2016 | ISBN: 1119015588 | 216 Pages | True PDF | 7 MB

Posted by **AlenMiler** at April 1, 2017

English | 20 Apr. 2017 | ISBN: 1498736645 | 412 Pages | PDF | 10.26 MB

Posted by **naag** at April 1, 2017

Springer | Computer Science | November 24, 2016 | ISBN-10: 3709107407 | 535 pages | pdf | 12.17 mb

Posted by **AlenMiler** at March 26, 2017

English | 14 Mar. 2017 | ISBN: 1893939758 | 408 Pages | PDF | 40.42 MB

Posted by **hill0** at March 21, 2017

English | 18 Apr. 2017 | ISBN: 3319530038 | 203 Pages | PDF | 12.96 MB

This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community.

Posted by **DZ123** at March 16, 2017

English | 2014 | ISBN: 3319097571 | PDF | pages: 145 | 3.4 mb

Posted by **naag** at March 14, 2017

Springer | Mathematics | Nov. 21 2016 | ISBN-10: 331929606X | 340 pages | pdf | 7.52 mb