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Online Infix Probability Computation for Probabilistic Finite Automata

机译:概率有限自动机的在线Infix概率计算

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Probabilistic finite automata (PFAs) are common statistical language model in natural language and speech processing. A typical task for PFAs is to compute the probability of all strings that match a query pattern. An important special case of this problem is computing the probability of a string appearing as a prefix, suffix, or infix. These problems find use in many natural language processing tasks such word prediction and text error correction. Recently, we gave the first incremental algorithm to efficiently compute the infix probabilities of each prefix of a string (Cognetta et al., 2018). We develop an asymptotic improvement of that algorithm and solve the open problem of computing the infix probabilities of PFAs from streaming data, which is crucial when processing queries online and is the ultimate goal of the incremental approach.
机译:概率有限自动机(PFAS)是自然语言和语音处理中的常见统计语言模型。 PFA的典型任务是计算与查询模式匹配的所有字符串的概率。这个问题的一个重要特殊情况是计算出现为前缀,后缀或infix的字符串的概率。这些问题在许多自然语言处理中找到了这样的单词预测和文本错误校正。最近,我们给出了第一个增量算法,以有效地计算字符串的每个前缀的infix概率(Cognetta等,2018)。我们开发了该算法的渐近改进,解决了从流数据计算PFA的INFIX概率的开放问题,这在在线处理查询时至关重要,并且是增量方法的最终目标。

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