Stochastic k-testable Tree Languages and Applications
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Tree k-Grammar Models for Natural Language Modelling and Parsing
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Parsing with Probabilistic Strictly Locally Testable Tree Languages
IEEE Transactions on Pattern Analysis and Machine Intelligence
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Journal of Computer and System Sciences
Deciding equivalence of top--down XML transformations in polynomial time
Journal of Computer and System Sciences
Smoothing and compression with stochastic k-testable tree languages
Pattern Recognition
DLT'03 Proceedings of the 7th international conference on Developments in language theory
Bisimulation minimization of tree automata
CIAA'06 Proceedings of the 11th international conference on Implementation and Application of Automata
Regular languages with variables on graphs
Information and Computation
Locality and the complexity of minimalist derivation tree languages
FG'10/FG'11 Proceedings of the 15th and 16th international conference on Formal Grammar
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We propose a generalization of the notion "deterministic" to "l-r-deterministic" for descending tree automata (also called root-to-frontier). The corresponding subclass of recognizable tree languages is characterized by a structural property that we name "homogeneous." Given a descending tree automaton recognizing a homogeneous tree language, it can be left-to-right (l-r) determinized and then minimized. The obtained minimal l-r-deterministic tree automaton is characterized algebraically. We exhibit a formal correspondence between the two evaluation modes on trees (ascending and descending) and the two on words (right-to-left and left-to-right). This is possible by embedding trees into the free monoid of pointed trees. We obtain a unified view of the theories of minimization of deterministic ascending and l-r-deterministic descending tree automata.