Single and Multiple Pattern String Matching Algorithm

Background/Objectives: Information Retrieval Systems (IRS) are playing an eminent role in different applications like World Wide Web, DNA sequence retrieval, etc. Basically, the IRS systems use the string matching algorithms. Methods/ Statistical Analysis: Since IRS uses string matching algorithms. If string matching algorithms quality is improved then automatically information retrieval system will achieve the most relevant results. For this retrieval purpose in this paper, single pattern and multiple pattern string matching algorithms are proposed. Findings: To assess the efficiency of the proposed single pattern and multiple pattern string matching algorithm in this paper, DNA sequences of different monkeys datasets called Saimiri boliviensis (2.46 Gb), Pan paniscus (2.71 Gb), Macaca nemestrina (2.78 Gb), Colobus angolensis palliates(2.8 Gb), Tarsius syrichta (3.31 Gb) are considered and different tetra patterns TAGA, TCTG are searched in this data sets. From the experimental results, it is observed that proposed single pattern and multiple pattern string matching algorithms outperforms compared to other well-known string matching algorithms. Application/Improvements: It is also observed that multiple pattern string matching algorithm reduces search time and unnecessary comparisons when compared to single pattern string matching and other existing string matching algorithms. These proposed algorithms very useful when we searching about the multiple patterns.