An Efficient Hashing Method for Exact String Matching Problems

Abstract

String matching is a crucial part of various important areas of computer science, and the aim is to find out every occurrence of a string within another string. String matching problems play an energetic role in many different areas such as intrusion detection within a network, identifying plagiarism, pattern recognition, data security, document searching, data mining, bioinformatics, speech exploration, and other various fields. There are two significant components of the string coordinating with calculations, which are the number of attempts and the number of character comparisons. The fundamental objective of our proposed method is to minimize both components. With these challenges, we have mobilized the good properties of Rabin Karp algorithm with our new searching technique which is named the EHM (Efficient Hashing Method) algorithm. At the analysis of performance, our algorithm shows a satisfactory result which is better than the BFM (Back and Forth Matching), MAC (Minimum Attempts and Comparisons), MS (Maximum Shift), and QS (Quick Search) algorithm. We have used different types of datasets such as DNA sequence, protein sequence, English text, etc., to analyze the performance.