Graph Algorithms and Applications
The mixture of data in real-life exhibits structure or connection property in nature. Typical data include biological data, communication network data, image data, etc. Graphs provide a natural way to represent and analyze these types of data and their relationships. Unfortunately, the related algor...
| Format: | eBook |
|---|---|
| Language: | English |
| Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Subjects: | |
| Online Access: | Open Access: DOAB: description of the publication Open Access: DOAB, download the publication |
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| 072 | 7 | |a KNTX |2 bicssc | |
| 072 | 7 | |a UY |2 bicssc | |
| 720 | 1 | |a Stefano, Gabriele Di |4 edt | |
| 720 | 1 | |a Cicerone, Serafino |4 edt | |
| 720 | 1 | |a Cicerone, Serafino |4 oth | |
| 720 | 1 | |a Stefano, Gabriele Di |4 oth | |
| 245 | 0 | 0 | |a Graph Algorithms and Applications |
| 260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2022 | ||
| 300 | |a 1 online resource (106 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | 0 | |a Open Access |f Unrestricted online access |2 star | |
| 520 | |a The mixture of data in real-life exhibits structure or connection property in nature. Typical data include biological data, communication network data, image data, etc. Graphs provide a natural way to represent and analyze these types of data and their relationships. Unfortunately, the related algorithms usually suffer from high computational complexity, since some of these problems are NP-hard. Therefore, in recent years, many graph models and optimization algorithms have been proposed to achieve a better balance between efficacy and efficiency. This book contains some papers reporting recent achievements regarding graph models, algorithms, and applications to problems in the real world, with some focus on optimization and computational complexity. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |u https://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Computer science |2 bicssc | |
| 650 | 7 | |a Information technology industries |2 bicssc | |
| 653 | |a analysis and design or graph algorithms | ||
| 653 | |a ancestral mixture model | ||
| 653 | |a clique independent set | ||
| 653 | |a clique transversal number | ||
| 653 | |a cliques | ||
| 653 | |a computational complexity of graph problems | ||
| 653 | |a computational social choice | ||
| 653 | |a congestion games | ||
| 653 | |a distance-hereditary graphs | ||
| 653 | |a distributed graph and network algorithms | ||
| 653 | |a election control | ||
| 653 | |a evolutionary tree | ||
| 653 | |a experimental evaluation of graph algorithms | ||
| 653 | |a forbidden subgraphs | ||
| 653 | |a graph theory with algorithmic applications | ||
| 653 | |a hole detection | ||
| 653 | |a influence maximization | ||
| 653 | |a k-fold clique transversal set | ||
| 653 | |a k-planarity | ||
| 653 | |a minus clique transversal function | ||
| 653 | |a mixture distance | ||
| 653 | |a mixture tree | ||
| 653 | |a multi-winner election | ||
| 653 | |a NP-hardness | ||
| 653 | |a paths | ||
| 653 | |a phylogenetic tree | ||
| 653 | |a planar graphs | ||
| 653 | |a polynomial time reduction | ||
| 653 | |a potential games | ||
| 653 | |a price of anarchy | ||
| 653 | |a price of stability | ||
| 653 | |a pure Nash equilibrium | ||
| 653 | |a recognition problem | ||
| 653 | |a signed clique transversal function | ||
| 653 | |a social influence | ||
| 653 | |a stretch number | ||
| 653 | |a tree comparison | ||
| 793 | 0 | |a DOAB Library. | |
| 856 | 4 | 0 | |u https://directory.doabooks.org/handle/20.500.12854/81106 |7 0 |z Open Access: DOAB: description of the publication |
| 856 | 4 | 0 | |u https://mdpi.com/books/pdfview/book/5135 |7 0 |z Open Access: DOAB, download the publication |