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

• Published in: Annals of data science Vol. 5; no. 2; pp. 181 - 207
• Main Authors: Raju, S. Viswanadha, Reddy, K. K. V. V. S., Rao, Chinta Someswara
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2018; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Business and Management; Data mining; Deoxyribonucleic acid; DNA; Economics; Finance; Gene sequencing; Information retrieval; Insurance; Linear arrays; Management; Pattern recognition; Statistics for Business; String matching; String matching with divide and conquer model; String matching; DNA; Parallel matching; Array based string matching model; String matching with butterfly model
• ISSN: 2198-5804; 2198-5812
• DOI: 10.1007/s40745-017-0124-1

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.