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Parallel String Matching with Linear Array, Butterfly and Divide and Conquer Models

机译:并行字符串匹配与线性数组,蝶形和分而治之模型

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摘要

String Matching is a technique of searching a pattern in a text. It is the basic concept to extract the fruitful information from large volume of text, which is used in different applications like text processing, information retrieval, text mining, pattern recognition, DNA sequencing and data cleaning etc., . Though it is stated some of the simple mechanisms perform very well in practice, plenty of research has been published on the subject and research is still active in this area and there are ample opportunities to develop new techniques. For this purpose, this paper has proposed linear array based string matching, string matching with butterfly model and string matching with divide and conquer models for sequential and parallel environments. To assess the efficiency of the proposed models, the genome sequences of different sizes (10–100 Mb) are taken as input data set. The experimental results have shown that the proposed string matching algorithms performs very well compared to those of Brute force, KMP and Boyer moore string matching algorithms.
机译:字符串匹配是一种在文本中搜索模式的技术。从大量文本中提取丰富的信息是一个基本概念,它被用于文本处理,信息检索,文本挖掘,模式识别,DNA测序和数据清理等各种应用中。尽管据说一些简单的机制在实践中表现良好,但是已经发表了大量关于该主题的研究,并且该领域的研究仍然活跃,并且有足够的机会开发新技术。为此,针对连续和并行环境,本文提出了基于线性数组的字符串匹配,蝶形模型的字符串匹配以及分而治之模型的字符串匹配。为了评估所提出模型的效率,将不同大小(10-100 Mb)的基因组序列作为输入数据集。实验结果表明,与Brute Force,KMP和Boyer Moore字符串匹配算法相比,所提出的字符串匹配算法具有很好的性能。

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