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Minimizing Deterministic Weighted Tree Automata

  • Andreas Maletti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5196)

Abstract

The problem of efficiently minimizing deterministic weighted tree automata (wta) is investigated. Such automata have found promising applications as language models in Natural Language Processing. A polynomial-time algorithm is presented that given a deterministic wta over a commutative semifield, of which all operations including the computation of the inverses are polynomial, constructs an equivalent minimal (with respect to the number of states) deterministic and total wta. If the semifield operations can be performed in constant time, then the algorithm runs in time O(rmn 4) where r is the maximal rank of the input symbols, m is the number of transitions, and n is the number of states of the input wta.

Keywords

Natural Language Processing Minimization Algorithm Congruence Relation Input Symbol Tree Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Andreas Maletti
    • 1
  1. 1.International Computer Science InstituteBerkeleyUSA

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