Experiments on the zero frequency problem

J. Cleary, W. Teahan
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引用次数: 35

Abstract

Summary form only given. A fundamental problem in the construction of statistical techniques for data compression of sequential text is the generation of probabilities from counts of previous occurrences. Each context used in the statistical model accumulates counts of the number of times each symbol has occurred in that context. So in a binary alphabet there will be two counts C/sub 0/ and C/sub 1/ (the number of times a 0 or 1 has occurred). The problem then is to take the counts and generate from them a probability that the next character will be a 0 or 1. A naive estimate of the probability of character i could be obtained by the ratio p/sub i/=C/sub i//(C/sub 0/+C/sub i/). A fundamental problem with this is that it will generate a zero probability if C/sub 0/ or C/sub 1/ is zero. Unfortunately, a zero probability prevents coding from working correctly as the "optimum" code length in this case is infinite. Consequently any estimate of the probabilities must be non-zero even in the presence of zero counts. This problem is called the zero frequency problem . A well known solution to the problem was formulated by Laplace and is known as Laplace's law of succession. We have investigated the correctness of Laplace's law by experiment.
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零频率问题的实验研究
只提供摘要形式。构建序列文本数据压缩的统计技术中的一个基本问题是从先前出现的计数中生成概率。统计模型中使用的每个上下文中都会累积每个符号在该上下文中出现的次数。因此,在二进制字母表中,有两个计数C/下标0/和C/下标1/(0或1出现的次数)。接下来的问题是获取计数并从中生成下一个字符为0或1的概率。对字符i的概率的朴素估计可以通过比值p/下标i/=C/下标i//(C/下标0/+C/下标i/)得到。一个基本的问题是,如果C/下标0/或C/下标1/为零,它将产生零概率。不幸的是,零概率会阻止编码正常工作,因为在这种情况下“最佳”代码长度是无限的。因此,即使存在零计数,对概率的任何估计也必须是非零的。这个问题被称为零频率问题。这个问题的一个众所周知的解决方案是由拉普拉斯公式化的,被称为拉普拉斯演替定律。我们用实验研究了拉普拉斯定律的正确性。
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