By Shi M., Yuan X., Cai M.

Show description

Read Online or Download (3,k)-Factor-Critical Graphs and Toughness PDF

Best graph theory books

Read e-book online Small worlds: the dynamics of networks between order and PDF

We all know the small-world phenomenon: quickly after assembly a stranger, we're stunned to find that we have got a mutual good friend, or we're hooked up via a quick chain of associates. In his booklet, Duncan Watts makes use of this fascinating phenomenon--colloquially referred to as "six levels of separation"--as a prelude to a extra basic exploration: lower than what stipulations can a small international come up in any form of community?

Graph Algorithms - download pdf or read online

Shimon Even's Graph Algorithms, released in 1979, used to be a seminal introductory e-book on algorithms learn by way of every body engaged within the box. This completely revised moment version, with a foreword by means of Richard M. Karp and notes by means of Andrew V. Goldberg, keeps the outstanding presentation from the 1st version and explains algorithms in a proper yet easy language with an instantaneous and intuitive presentation.

The Reconstruction of Trees from Their Automorphism Groups by Matatyahu Rubin PDF

Bushes, often referred to as semilinear orders, are in part ordered units within which each preliminary section made up our minds via a component is linearly ordered. This booklet makes a speciality of automorphism teams of timber, offering an almost entire research of whilst bushes have isomorphic automorphism teams. specified consciousness is paid to the category of $\aleph_0$-categorical bushes, and for this category the research is entire.

Additional resources for (3,k)-Factor-Critical Graphs and Toughness

Example text

The synopsis construction is typically defined through either node or edge contractions. The key is to define a synopsis which retains the relevant structural property of the underlying graph. In [7], the algorithm in [177] is used in order to collapse the dense regions of the graph, and represent the summarized graph in terms of sparse regions. The resulting contracted graph still retains important structural properties such as the connectivity of the graph. In [46], a randomized summarization technique is used in order to determine frequent patterns in the underlying graph.

This summarization is then leveraged in order to determine the frequent subgraph patterns from the data. Bounds are derived in [46] on the false positives and false negatives with the use of such an approach. Another challenging variation is when the frequent patterns are overlaid on a very large graph, as a result of which patterns may themselves be very large subgraphs. An algorithm called TSMiner was proposed in [110] to determine frequent structures in very large scale graphs. Graph pattern mining has numerous applications for a variety of applications.

Matsumoto. An Application of Boosting to Graph Classification, NIPS Conf. 2004. [19] J. Leskovec, J. Kleinberg, C. Faloutsos. Graph Evolution: Densification and Shrinking Diameters. ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 1(1), 2007. [20] K. Liu and E. Terzi. Towards identity anonymization on graphs. ACM SIGMOD Conference 2008. [21] R. Kumar, P Raghavan, S. Rajagopalan, D. Sivakumar, A. Tomkins, E. Upfal. The Web as a Graph. ACM PODS Conference, 2000. An Introduction to Graph Data 11 [22] S.

Download PDF sample

(3,k)-Factor-Critical Graphs and Toughness by Shi M., Yuan X., Cai M.

by Paul

Rated 4.76 of 5 – based on 49 votes