Results 11 to 20 of about 3,546,741 (346)
An interval graph is a comparability graph
Journal of Combinatorial Theory, 1969 M. Jean
semanticscholar +5 more sources
Closed graphs are proper interval graphs [PDF]
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2014 Let G be a connected simple graph. We prove that G is a closed graph if and only if G is a proper interval graph. As a consequence we obtain that there exist linear-time algorithms for closed graph recognition.
Crupi Marilena, Rinaldo Giancarlo
doaj +6 more sources
Discrete Mathematics, 1982 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Henry Martyn Mulder
openalex +3 more sources
A Characterization of Comparability Graphs and of Interval Graphs [PDF]
Canadian Journal of Mathematics, 1964 Let < be a non-reflexive partial ordering defined on a set P. Let G(P, <) be the undirected graph whose vertices are the elements of P, and whose edges (a, b) connect vertices for which either a < b or b < a. A graph G with vertices P for which there exists a partial ordering < such that G = G(P, <) is called a comparability graph.In §
Paul C. Gilmore, Alan J. Hoffman
openalex +4 more sources
International Journal of Data Mining, Modelling and Management, 2018 Frequent subgraph mining is a difficult data mining problem aiming to find the exact set of frequent subgraphs into a database of graphs. Current subgraph mining approaches make use of the canonical encoding which is one of the key operations. It is well known that canonical encodings have an exponential time complexity.
Amina Kemmar, Yahia Lebbah, S. Loudni
semanticscholar +4 more sources
An evolution of interval graphs
Discrete Mathematics, 1990 AbstractWe present a model for random interval graphs which, like the model of Erdös and Rényi, exhibits an evolution from empty graphs to complete graphs. We determine various thresholds, including the common threshold for isolated vertices and connectivity.
Edward R. Scheinerman
openalex +3 more sources
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks [PDF]
Neural Information Processing Systems, 2023 Graph Neural Networks (GNNs) are powerful machine learning prediction models on graph-structured data. However, GNNs lack rigorous uncertainty estimates, limiting their reliable deployment in settings where the cost of errors is significant.
Kexin Huang +3 more
semanticscholar +1 more source
An interval graph is not a comparability graph
Journal of Combinatorial Theory, 1970 P. Fishburn
semanticscholar +3 more sources
On some subclasses of interval catch digraphs
Electronic Journal of Graph Theory and Applications, 2022 A digraph G = (V, E) is an interval catch digraph if for each vertex v ∈ V, one can associate an interval on real line and a point within it (say (Iv, pv)) in such a way that uv ∈ E if and only if pv ∈ Iu. It was introduced by Maehara in 1984.
Sanchita Paul, Shamik Ghosh
doaj +1 more source
International Journal of Mathematics for Industry, 2022 [Formula: see text]-labeling problem ([Formula: see text]-[Formula: see text]) is an important topic in discrete mathematics due to its various applications, like in frequency assignment in mobile communication systems, signal processing, circuit design,
Sk. Amanathulla +2 more
doaj +1 more source