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  • 1.
    Chiang, David
    et al.
    University of Notre Dame.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Gildea, Daniel
    University of Rochester.
    Lopez, Adam
    University of Edinburgh.
    Satta, Giorgio
    University of Padua.
    Weighted DAG automata for semantic graphs2018In: Computational linguistics - Association for Computational Linguistics (Print), ISSN 0891-2017, E-ISSN 1530-9312, Vol. 44, no 1, p. 119-186Article in journal (Refereed)
    Abstract [en]

    Graphs have a variety of uses in natural language processing, particularly as representations of linguistic meaning. A deficit in this area of research is a formal framework for creating, combining, and using models involving graphs that parallels the frameworks of finite automata for strings and finite tree automata for trees. A possible starting point for such a framework is the formalism of directed acyclic graph (DAG) automata, defined by Kamimura and Slutzki and extended by Quernheim and Knight. In this article, we study the latter in depth, demonstrating several new results, including a practical recognition algorithm that can be used for inference and learning with models defined on DAG automata. We also propose an extension to graphs with unbounded node degree and show that our results carry over to the extended formalism.

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