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Ann Comb, 2013 We work out a graph limit theory for dense interval graphs. The theory developed departs from the usual description of a graph limit as a symmetric function W(x, y) on the unit square, with x and y uniform on the interval (0, 1).
Diaconis P, Holmes S, Janson S.
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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
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A new haplotype block detection method for dense genome sequencing data based on interval graph modeling of clusters of highly correlated SNPs. [PDF]
Bioinformatics, 2018 Kim SA, Cho CS, Kim SR, Bull SB, Yoo YJ.
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A Note on the Interval Function of a Disconnected Graph
Discussiones Mathematicae Graph Theory, 2018 In this note we extend the Mulder-Nebeský characterization of the interval function of a connected graph to the disconnected case. One axiom needs to be adapted, but also a new axiom is needed in addition.
Changat Manoj +3 more
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Discrete Mathematics, 1982 AbstractLet G be a graph on v labelled vertices with E edges, without loops or multiple edges. Let v → ∞ and let E=E(v) be a function of v such that lim E(v)v23=c. The limit of the probability that a random graph is a unit interval graph, indifference graph or proper interval graph is exp(−43c3).
J. Cohen
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Time Interval-Enhanced Graph Neural Network for Shared-Account Cross-Domain Sequential Recommendation [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 Shared-account cross-domain sequential recommendation (SCSR) task aims to recommend the next item via leveraging the mixed user behaviors in multiple domains.
Lei Guo +5 more
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Learning semantic program embeddings with graph interval neural network [PDF]
Proc. ACM Program. Lang., 2020 Learning distributed representations of source code has been a challenging task for machine learning models. Earlier works treated programs as text so that natural language methods can be readily applied.
Yu Wang +3 more
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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
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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
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Signless Laplacian Energy of Interval-Valued Fuzzy Graph and its Applications
Sains Malaysiana, 2023 An interval-valued fuzzy graph (IVFG) emanates from a fuzzy graph (FG) where the membership is given in interval form. This framework give the user more flexibility in dealing with fuzzy information.
M. Romdhini +4 more
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