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  Graph Inference from Walks

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by Osamu Maruyama
http://www.i.kyushu-u.ac.jp/TR/123.ps.Z
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Abstract:

Let G be an edge-colored graph. A walk on G is a path in G containing all edges of G. The trace of a path in G is the sequence of the edge-colors seen in the path. The graph inference from a walk is the problem of, given a string x of colors, finding an edge-colored graph with the minimum number of edges which realizes a walk with trace x. This thesis is devoted to the study of the graph inference from a walk and its modified versions called the graph inference from partial walks and the walk realizability problem. Here, a partial walk on a graph is a path in the graph. These graph inference problems are closely related to inferring a Markov chain from its output, the identification of a finite state automaton from its input/output behavior, and the problem of constructing an edge-weighted graph from distance data. For the graph inference from a walk, all results so far known are concerned with degree-bounded graphs as follows: (i) Raghavan gave an O(n log n)-time algorithm to solve the graph inference from a walk for graphs of bounded degree two, which are

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