Quantitative graph theory : : mathematical foundations and applications / / edited by Matthias Dehmer, Frank Emmert-Streib.
"Graph-based approaches have been employed extensively in several disciplines such as biology, computer science, chemistry, and so forth. In the 1990s, exploration of the topology of complex networks became quite popular and was triggered by the breakthrough of the Internet and the examinations...
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Superior document: | Discrete mathematics and its applications |
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TeilnehmendeR: | |
Place / Publishing House: | Boca Raton : : CRC Press,, [2015] 2015 |
Year of Publication: | 2015 |
Language: | English |
Series: | Discrete mathematics and its applications.
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Online Access: | |
Physical Description: | 1 online resource (516 pages) :; illustrations. |
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245 | 0 | 0 | |a Quantitative graph theory : |b mathematical foundations and applications / |c edited by Matthias Dehmer, Frank Emmert-Streib. |
264 | 1 | |a Boca Raton : |b CRC Press, |c [2015] | |
264 | 4 | |c 2015 | |
300 | |a 1 online resource (516 pages) : |b illustrations. | ||
336 | |a text |2 rdacontent | ||
337 | |a computer |2 rdamedia | ||
338 | |a online resource |2 rdacarrier | ||
490 | 1 | |a Discrete mathematics and its applications | |
504 | |a Includes bibliographical references and index. | ||
520 | |a "Graph-based approaches have been employed extensively in several disciplines such as biology, computer science, chemistry, and so forth. In the 1990s, exploration of the topology of complex networks became quite popular and was triggered by the breakthrough of the Internet and the examinations of random networks. As a consequence, the structure of random networks has been explored using graph-theoretic methods and stochastic growth models. However, it turned out that besides exploring random graphs, quantitative approaches to analyze networks are crucial as well. This relates to quantifying structural information of complex networks by using ameasurement approach. As demonstrated in the scientific literature, graph- and informationtheoretic measures, and statistical techniques applied to networks have been used to do this quantification. It has been found that many real-world networks are composed of network patterns representing nonrandom topologies.Graph- and information-theoretic measures have been proven efficient in quantifying the structural information of such patterns. The study of relevant literature reveals that quantitative graph theory has not yet been considered a branch of graph theory"-- |c Provided by publisher. | ||
588 | |a Description based on print version record. | ||
590 | |a Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. | ||
650 | 0 | |a Graph theory |x Data processing. | |
650 | 0 | |a Combinatorial analysis. | |
655 | 4 | |a Electronic books. | |
700 | 1 | |a Dehmer, Matthias, |d 1968- |e editor. | |
700 | 1 | |a Emmert-Streib, Frank, |e editor. | |
776 | 0 | 8 | |i Print version: |t Quantitative graph theory : mathematical foundations and applications. |d Boca Raton : CRC Press, [2015] |k Discrete mathematics and its applications |z 9781466584518 |w (DLC)10961798 |
797 | 2 | |a ProQuest (Firm) | |
830 | 0 | |a Discrete mathematics and its applications. | |
856 | 4 | 0 | |u https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=1591690 |z Click to View |