Multimodal Analytical Approach for Determination of Deduplication in Names for Identifying People during Emergency Situations
Multimodal Analytical Approach for Determination of Deduplication in Names for Identifying People during Emergency Situations |
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| © 2025 by IJETT Journal | ||
| Volume-73 Issue-8 |
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| Year of Publication : 2025 | ||
| Author : Nagesh Raykar, Prema Sahane, Sonali Rangdale, Dipmala Salunke, Pallavi Tekade, Pramod Patil | ||
| DOI : 10.14445/22315381/IJETT-V73I8P101 | ||
How to Cite?
Nagesh Raykar, Prema Sahane, Sonali Rangdale, Dipmala Salunke, Pallavi Tekade, Pramod Patil, "Multimodal Analytical Approach for Determination of Deduplication in Names for Identifying People during Emergency Situations," International Journal of Engineering Trends and Technology, vol. 73, no. 8, pp.1-13, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I8P101
Abstract
Phonetic algorithms are developed to index words based on their pronunciation and are primarily developed for the English language. Demographic Data (DD) gives information about people according to certain attributes like name, age, gender, residence, occupation, etc. In hospitals, government record matching, and multilingual information retrieval systems during emergency situations, it becomes vital to quickly and accurately identify a person, and many times, confusion is created due to duplication in records. The records do not fetch the names if their alphabetical order is incorrect while writing the same names. Phonetic name identification also provides important statistics in web analysis. Though there are many existing studies handling the DD, no specific study has been done to deal with the Indian regional language. The proposed research compares the conventional regional names of format First Name (FN) and Last Name (LN) based on the phonetic rule. Research proposed a novel, efficient phonetic-based algorithm for the regional language. Attempts have been made to prevent name repetition and similar names, even with different alphabetical arrangements. There are emergency situations, especially while finding a next of kin, finding a person during national security issues, or in any emergency situation when not much information is available, but locating a person or informing the family about the situation is important. Many times, the person’s information is available, but the database does not fetch it if there is a dissimilarity in the spellings of the names. This research is trying to apply multimodal approaches to combine NLP and machine learning approaches for identifying people during emergency situations. Results from the suggested approach are promising, and for a real-time environment, it can be applied.
Keywords
Demographic, Indexing, Indian regional languages, Machine Learning, Natural Language Processing (NLP), Phonetic algorithm.
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