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The behavior of a Markov network with respect to an absorbing class: the target algorithm

Giacomo Aletti (2009)

RAIRO - Operations Research

In this paper, we face a generalization of the problem of finding the distribution of how long it takes to reach a “target” set T of states in Markov chain. The graph problems of finding the number of paths that go from a state to a target set and of finding the n-length path connections are shown to belong to this generalization. This paper explores how the state space of the Markov chain can be reduced by collapsing together those states that behave in the same way for the purposes of calculating...

The Orderly Colored Longest Path Problem – a survey of applications and new algorithms

Marta Szachniuk, Maria Cristina De Cola, Giovanni Felici, Jacek Blazewicz (2014)

RAIRO - Operations Research - Recherche Opérationnelle

A concept of an Orderly Colored Longest Path (OCLP) refers to the problem of finding the longest path in a graph whose edges are colored with a given number of colors, under the constraint that the path follows a predefined order of colors. The problem has not been widely studied in the previous literature, especially for more than two colors in the color arrangement sequence. The recent and relevant application of OCLP is related to the interpretation of Nuclear Magnetic Resonance experiments for...

TPM: Transition probability matrix - Graph structural feature based embedding

Sarmad N. Mohammed, Semra Gündüç (2023)

Kybernetika

In this work, Transition Probability Matrix (TPM) is proposed as a new method for extracting the features of nodes in the graph. The proposed method uses random walks to capture the connectivity structure of a node's close neighborhood. The information obtained from random walks is converted to anonymous walks to extract the topological features of nodes. In the embedding process of nodes, anonymous walks are used since they capture the topological similarities of connectivities better than random...

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