Mobile-Based Word Matching Detection using Intelligent Predictive Algorithm

Abstract

Word matching is a string searching technique for information retrieval in Natural Language Processing (NLP). There are several algorithms have been used for string search and matching such as Knuth Morris Pratt, Boyer Moore, Horspool, Intelligent Predictive and many other. However, there some issues need to be considered in measuring the performance of the algorithms such as the efficiency for searching small alphabets, time taken in processing the pattern of the text and extra space to support a huge table or state machines. Intelligent Predictive (IP) algorithm capable to solve several word matching issues discovered in other string searching algorithms especially with abilities to skip the pre-processing of the pattern, uses simple rules during matching process and does not involved complex computations. Due to those reasons, IP algorithm is used in this study due to the ability of this algorithm to produce a good result in string searching process.  This article aims to apply IP algorithm together with Optical Character Recognition (OCR) tool for mobile-based word matching detection. There are four phases in this study consists of data preparation, mobile based system design, algorithm implementation and result analysis. The efficiency of the proposed algorithm was evaluated based on the execution time of searching process among the selected algorithms. The result shows that the IP algorithm for string searching process is more efficient in execution time compared to well-known algorithm i.e. Boyer Moore algorithm. In future work, the performance of string searching process can be enhanced by using other suitable optimization searching techniques such as Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization and many others.