Clustering oriented hashing based multiple string pattern matching algorithm

Multiple string pattern matching aims at searching all occurrence of pattern set P in large data set (or text) T. Previous paper presented a new hashing based adaptive algorithm which perform search in order O(n/k) where n is length of T and k is the minimum length among all patterns in set P. This paper presents an idea of clustering the pattern set prior to searching phase. Implementation shows search speed up by more than 400%. This case study consists of search set with more than 420,000 characters. It also identifies various factors which effects search time and establishes mathematical relationship among them. It helps to theoretically determine the speed up in search time in comparison to that taken by using non-clustering approach. Experimental result shows that practical results are synchronous with respect to theoretical predictions hence proves accuracy of the mathematical establishment.