论文标题
非确定功能性换能器推理算法
Nondeterministic functional transducer inference algorithm
论文作者
论文摘要
本文的目的是提出一种推断非确定功能传感器的算法。它与其他知名算法有很多共同点，例如RPNI和OSTIA。的确，我们将争辩说，这种算法是它们两者的概括。功能传感器都是那些不确定性的换能器，其规则关系是一个函数。 EPSILON过渡以及随后的输出可以删除此类机器，除了丢失空字符串的输出外。从阴性示例中学习部分功能传感器等同于从正面数据中学习总数。
The purpose of this paper is to present an algorithm for inferring nondeterministic functional transducers. It has a lot in common with other well known algorithms such has RPNI and OSTIA. Indeed we will argue that this algorithm is a generalisation of both of them. Functional transducers are all those nondeterministic transducers whose regular relation is a function. Epsilon transitions as well as subsequential output can be erased for such machines, with the exception of output for empty string being lost. Learning partial functional transducers from negative examples is equivalent to learning total from positive-only data.
