Exact pattern matching algorithms are popular and used widely in several applications, such as molecular biology, text processing, image processing, web search engines, network intrusion detection systems and operating systems. The focus of these algorithms is to achieve time efficiency according to applications but not memory consumption. In this work, we propose a novel idea to achieve both time efficiency and memory consumption by splitting query string for searching in Corpus. For a given text, the proposed algorithm split the query pattern into two equal halves and considers the second (right) half as a query string for searching in Corpus. Once the match is found with second halves, the proposed algorithm applies brute force procedure to find remaining match by referring the location of right half. Experimental results on different >S1 Dataset, namely Arabic, English, Chinese, Italian and French text databases show that the proposed algorithm outperforms the existing >S1 Algorithm in terms of time efficiency and memory consumption as the length of the query pattern increases.
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机译：精确模式匹配算法非常流行，并广泛用于多种应用中，例如分子生物学，文本处理，图像处理，Web搜索引擎，网络入侵检测系统和操作系统。这些算法的重点是实现根据应用程序的时间效率，而不是内存消耗。在这项工作中，我们提出了一种新颖的想法，即通过在查询语料库中拆分查询字符串来实现时间效率和内存消耗。对于给定的文本，所提出的算法将查询模式分为两个相等的部分，并将后半部分（右半部分）作为用于在语料库中进行搜索的查询字符串。一旦发现与后半部分匹配，则所提出的算法通过参考右半部分的位置，应用蛮力程序来查找剩余的匹配项。在不同的> S1数据集（即阿拉伯文，英文，中文，意大利文和法文文本数据库）上的实验结果表明，该算法在时间效率和时间方面都优于现有的> S1 A 算法。随着查询模式长度的增加，内存消耗也会增加。
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