非确定性函数传感器推理算法
Nondeterministic functional transducer inference algorithm
摘要：
本文的目的是提出一个算法推断非确定性功能传感器。它与其他知名算法有很多共同点，例如RPNI和OSTIA。事实上，我们将认为，这个算法是他们两个的概括。函数变换器是指所有正则关系为函数的非确定性变换器。对于这样的机器，除了空字符串的输出丢失之外，Epperimental转换以及基本输出都可以被擦除。从阴性示例学习部分功能换能器等同于从仅阳性数据学习总体。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
