An optimal algorithm for generating minimal perfect hash functions
Information Processing Letters
C4.5: programs for machine learning
C4.5: programs for machine learning
Fast algorithms for sorting and searching strings
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Machine Learning
Handbook of Formal Languages
Using Tries to Eliminate Pattern Collisions in Perfect Hashing
IEEE Transactions on Knowledge and Data Engineering
A Trie Compaction Algorithm for a Large Set of Keys
IEEE Transactions on Knowledge and Data Engineering
Incremental construction of minimal acyclic finite-state automata
Computational Linguistics - Special issue on finite-state methods in NLP
Finite-state transducers in language and speech processing
Computational Linguistics
On some applications of finite-state automata theory to natural language processing
Natural Language Engineering
| Hi-index | 0.00 |
Finite-state transducers can be used to map a language onto a set of values. This paper proposes an alternate representation method for such a mapping, consisting of associating a finite-state automaton accepting the input language with a decision tree representing the output values. The advantages of this approach are that it leads to more compact representations than transducers, and that decision trees can easily be synthesized by machine learning techniques.