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Informative Article | Science and Technology | India | Volume 7 Issue 9, September 2018
Re-Ranking Matching Algorithm for Direct Certification Eligibility Determination
Abstract: This research paper introduces an advanced algorithm designed for optimizing eligibility determination in federal incentive programs called Direct Certification [1], with a focus on addressing discrepancies in personal identification information. The algorithm employs sophisticated names matching techniques, including Soundex [2], metaphone [3], phonetic matching [4], levenshtein distance [5] and then assigning weights based on confidence levels of the matching. Additionally, the application incorporates foster and household matching steps for improved identification of eligible candidates. The technical implementation includes cryptographic notations to encrypt data at rest, ensuring the security of personally identifiable information (PII). The paper also delves into performance improvements and latency reduction achieved through the algorithm, highlighting its efficacy in complex user interface interactions. Through this research, we present a comprehensive solution that not only enhances the accuracy of eligibility determination but also addresses crucial aspects of data security and system performance. This paper delves into the overall architecture [6], explicates design choices, and imparts insights into best practices for implementing and maintaining applications [7]. The discussion encompasses critical aspects of the application?s functionality, emphasizing the need for scalability, resilience, and security to meet the demands of modern software applications that will address these business scenarios.
Keywords: Direct Certification, Name Matching, Pattern Matching
Edition: Volume 7 Issue 9, September 2018,
Pages: 1657 - 1660