Subsequential transducers: a coalgebraic perspective

Minimizing subsequential transducers: a survey

Coalgebraising Subsequential Transducers

Actively Learning Probabilistic Subsequential Transducers

In this paper we investigate learning of probabilistic subsequential transducers in an active learning environment. In our learning algorithm the learner interacts with an oracle by asking probabilistic queries on the observed data. We prove our algorithm in an identification in the limit model. We also provide experimental evidence to show the correctness and to analyze the learnability of the...

Efficient dictionary-based text rewriting using subsequential transducers

Problems in the area of text and document processing can often be described as text rewriting tasks: given an input text, produce a new text by applying some fixed set of rewriting rules. In its simplest form, a rewriting rule is given by a pair of strings, representing a source string (the “original”) and its substitute. By a rewriting dictionary, we mean a finite list of such pairs; dictionar...

Learning Subsequential Transducers for Pattern Recognition Interpretation Tasks

The “interpretation” framework in pattern recognition (PR) arises in the many cases in which the more classical paradigm of “classification” is not properly applicable generally because the number of classes is rather large or simply because the concept of “class” does not hold. A very general way of representing the results of interpretations of given objects or data is in terms of sentences o...