Intelligent Predictive String Search Algorithm

Text processing has moved beyond merely word processing and desktop publishing softwares, which currently form a miniscule part of its application. With the advent of the internet and the huge amount of text processing associated with information mining, string search algorithms have gained importance. In this paper a new string searching algorithm is presented that uses intelligent predictions based on text features to search for a string in a text. The proposed algorithm has been developed after analyzing the existing algorithms such as KMP, Boyer-Moore and Horspool. One unique feature of this algorithm is that unlike the existing algorithms, it does not require pre-processing the pattern to be searched. As a result it does not incur the overhead required in pre-processing the pattern. The algorithm searches through a given text to find the first occurrence of a pattern. It does not involve complex computations and uses simple rules during a match or mismatch of a pattern character. Based on the variety of applications coming up in areas of data and information mining, sentiment analysis, DNA pattern matching etc, this simple, elegant and intelligent algorithm will find its application.