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An analysis of the Intelligent Predictive String Search Algorithm: A Probabilistic Approach

机译:智能预测字符串搜索算法的分析:一种概率方法

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Due to the huge surge of digital information and the task of mining valuable information from huge amount of data, text processing tasks like string search has gained importance. Earlier techniques for text processing relied on following some predetermined sequence of steps or some hard coded rules. However, these techniques might soon prove to be inefficient as the amount of data generated by modern computer systems in increasing more and more. One solution to this problem lies in the development of intelligent algorithms that incorporate a certain degree of intelligence and unlike traditional algorithm are able to cope up with changing scenarios. This paper presents a string searching algorithm that incorporates a certain degree of intelligence to search for a string in a text. In the search of a string, the algorithm relies on a chance process and a certain probability at each step. An analysis of the algorithm based on the approach suggested by A. A. Markov is also presented in the paper. The expected number of average comparisons required for searching a string in a text is computed. Based on the varieties of applications that are coming up in the area of text processing and the related fields, this new algorithm aims to find its use.
机译:由于数字信息的激增和从大量数据中挖掘有价值的信息的任务,诸如字符串搜索之类的文本处理任务变得越来越重要。较早的文本处理技术依赖于一些预定的步骤序列或一些硬编码的规则。但是,随着现代计算机系统生成的数据量越来越多,这些技术可能很快就会被证明效率低下。解决该问题的一种方法是开发具有一定智能程度的智能算法,并且与传统算法不同,它能够应对不断变化的情况。本文提出了一种字符串搜索算法,该算法结合了一定程度的智能以在文本中搜索字符串。在搜索字符串时,该算法在每个步骤中都依赖机会过程和确定的概率。本文还对基于A. A. Markov提出的方法的算法进行了分析。计算在文本中搜索字符串所需的平均比较的预期数量。基于文本处理和相关领域中出现的各种应用程序,该新算法旨在找到其用途。

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