Abstract
We conduct a comparative study of two state-of-the-art algorithms for extracting the N best trees from a weighted tree automaton (wta). The algorithms are Best Trees, which uses a priority queue to structure the search space, and Filtered Runs, which is based on an algorithm by Huang and Chiang that extracts N best runs, implemented as part of the Tiburon wta toolkit. The experiments are run on four data sets, each consisting of a sequence of wtas of increasing sizes. Our conclusion is that Best Trees can be recommended when the input wtas exhibit a high or unpredictable degree of nondeterminism, whereas Filtered Runs is the better option when the input wtas are large but essentially deterministic.
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Notes
- 1.
In [1] the term smallest completion was used.
- 2.
- 3.
For the sake of clarity, the expression is slightly simplified. In particular, the maximum rank r of symbols is taken to be constant, as it is typically small in practise.
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Björklund, J., Drewes, F., Jonsson, A. (2018). A Comparison of Two N-Best Extraction Methods for Weighted Tree Automata. In: Câmpeanu, C. (eds) Implementation and Application of Automata. CIAA 2018. Lecture Notes in Computer Science(), vol 10977. Springer, Cham. https://doi.org/10.1007/978-3-319-94812-6_9
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