000			02863nam a22003618i 4500
001			CR9781316339831
003			UkCbUP
005			20200124160213.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			150126s2015||||enk o ||1 0|eng|d
020			_a9781316339831 (ebook)
020			_z9781107118508 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA166.17 _b.F75 2015
082	0	0	_a511/.5 _223
100	1		_aFrieze, Alan, _d1945- _eauthor.
245	1	0	_aIntroduction to random graphs / _cAlan Frieze, Carnegie-Mellon University, Pennsylvania, Michał Karoński, Adam Mickiewicz University and Emory University.
264		1	_aCambridge : _bCambridge University Press, _c2015.
300			_a1 online resource (xvii, 464 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 01 Feb 2016).
505	8		_aMachine generated contents note: Preface; Part I. Basic Models: 1. Random graphs; 2. Evolution; 3. Vertex degrees; 4. Connectivity; 5. Small subgraphs; 6. Spanning subgraphs; 7. Extreme characteristics; 8. Extremal properties; Part II. Basic Model Extensions: 9. Inhomogeneous graphs; 10. Fixed degree sequence; 11. Intersection graphs; 12. Digraphs; 13. Hypergraphs; Part III. Other Models: 14. Trees; 15. Mappings; 16. k-out; 17. Real-world networks; 18. Weighted graphs; 19. Brief notes on uncovered topics; Part IV. Tools and Methods: 20. Moments; 21. Inequalities; 22. Differential equations method; 23. Branching processes; 24. Entropy; References; Author index; Main index.
520			_aFrom social networks such as Facebook, the World Wide Web and the Internet, to the complex interactions between proteins in the cells of our bodies, we constantly face the challenge of understanding the structure and development of networks. The theory of random graphs provides a framework for this understanding, and in this book the authors give a gentle introduction to the basic tools for understanding and applying the theory. Part I includes sufficient material, including exercises, for a one semester course at the advanced undergraduate or beginning graduate level. The reader is then well prepared for the more advanced topics in Parts II and III. A final part provides a quick introduction to the background material needed. All those interested in discrete mathematics, computer science or applied probability and their applications will find this an ideal introduction to the subject.
650		0	_aRandom graphs.
650		0	_aCombinatorial probabilities.
650		0	_aProbabilities.
700	1		_aKaroński, Michał, _eauthor.
776	0	8	_iPrint version: _z9781107118508
856	4	0	_uhttps://doi.org/10.1017/CBO9781316339831
999			_c516009 _d516007