Adapting Soundex for Arabic Names with Preprocessing for Better Accuracy

Abstract

The Soundex algorithm plays an important role in retrieving names based on phonetic similarity, as it converts names into numerical representations that facilitate comparison based on pronunciation rather than exact spelling. This algorithm helps identify names that sound similar despite variations in their spelling, improving the accuracy of searches in databases. Although initially used for languages like English, it has been adapted to fit the characteristics of other languages, such as Arabic. For Arabic names, the algorithm is enhanced to handle variations in pronunciation and spelling, further improving retrieval effectiveness. In this way, the Soundex algorithm provides an efficient method for classifying and retrieving names based on their phonetic sound rather than relying solely on exact spelling. We developed a system based on preliminary processing of Arabic names to improve precision and recall, taking into account the unique characteristics of the Arabic language. We compiled a list of Arabic names, which were then divided into groups based on their phonetic pronunciation. The proposed system demonstrated effectiveness and accuracy in retrieving and classifying names. Overall, the system showed good performance, with a need for improvements in certain specific cases.