Entity Matching

Entity matching aims to identify records across different datasets that refer to the same real-world entity, a crucial task in data integration and cleaning. Current research focuses on leveraging large language models (LLMs) for improved accuracy and efficiency, exploring various prompt engineering techniques, fine-tuning strategies, and the incorporation of graph-based methods to handle complex relationships between entities. This field is significant because accurate entity matching is essential for numerous applications, including customer relationship management, financial analysis, and biomedical research, ultimately improving data quality and enabling more effective data-driven insights.