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Personal Identity Matching

Authors

Mazin Al-Shuaili and Marco Carvalho, Florida Institute of Technology, USA

Abstract

Despite all existing methods to identify a person, such as fingerprint, iris, and facial recognition, the personal name is still one of the most common ways to identify an individual. In this paper, we propose two novel algorithms: The first one uses sound techniques to create a multi-dimensional vector representation of names to compute a degree of similarity. This algorithm compares names that are written in different languages (cross-language) and transliterated names in English. The second algorithm builds on the first one and measures the similarities between full names, taking into account the full name structure. We evaluate the algorithms for transliterated names and across languages using Arabic and English as an example. Significant results are achieved by both algorithms compared with other existing algorithms.

Keywords

Border Security, Cross-Language Information Retrieval, Information Retrieval, Security Screening System.

Full Text  Volume 6, Number 2