Entity Matching for Digital World: A Modern Approach using Artificial Intelligence and Machine Learning
Entity Matching for Digital World: A Modern Approach using Artificial Intelligence and Machine Learning
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Keywords

entity matching
entity resolution
record linkage
de-duplication
machine learning

How to Cite

K. Victor Rajan, & Edward Lambert. (2023). Entity Matching for Digital World: A Modern Approach using Artificial Intelligence and Machine Learning. Global Journal of Computer Science and Technology, 23(D1), 35–44. Retrieved from https://gjcst.com/index.php/gjcst/article/view/34

Abstract

Entity matching is the field of research solving the problem of identifying similar records which refer to the same real-world entity In today s digital world business organizations deal with large amount of data like customers vendors manufacturers etc Entities are spread across various data sources and failure to correlate two records as one entity can lead to confusion Relationships and patterns would be missed Aggregations and calculations won t make any sense It is a significant data integration effort that often arises when data originate from different sources In such scenarios we understand the situation by linking records and then track entities from a person to a product etc There is appreciable value in integrating the data silos across various industries
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