Abstract
Researchers confront major problems while searching for various kinds of data in large imprecise databases, as they are not spelled correctly or in the way they were expected to be spelled. As a result, they cannot find the word they sought. Over the years of struggle, pronunciation of words was considered as one of the practices to solve the problem effectively. The technique used to acquire words based on sounds is known as “Phonetic Matching”. Soundex was the first algorithm developed and other algorithms such as Metaphone, Caverphone, DMetaphone, Phonex etc., are also used for information retrieval in different environments. The main contribution of this paper is to analyze and implement the newly proposed MetaSoundex algorithm for fixing ill-defined data in English and Spanish languages. The newly developed MetaSoundex algorithm addresses the limitations of well-known phonetic matching techniques, Metaphone and Soundex. Specifically, the new algorithm provided results that are more accurate compared to both Soundex and Metaphone algorithms and has higher precision compared to Soundex, thus reducing the noise in the considered arena.
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