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Proceedings of International Joint Conference on Neural Networks, San Jose, California, USA, July 31 ? August 5, 2011, Beyond Probabilistic Record Linkage: Using Neural Networks and Complex Features
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Beyond probabilistic record linkage refers to advanced techniques and methods used to establish connections between records that go beyond traditional probabilistic matching algorithms. It involves the use of additional data sources, machine learning, and other approaches to enhance the accuracy and efficiency of record linkage processes.
Entities or organizations that are involved in data linkage or cross-referencing multiple datasets are typically required to file beyond probabilistic record linkage. This can include government agencies, research institutions, healthcare providers, and other entities that handle large amounts of data and need to establish linkages between different records.
Filling out beyond probabilistic record linkage involves a multi-step process that typically includes gathering the necessary data, preprocessing and cleaning the data, selecting and applying appropriate record linkage algorithms or techniques, and evaluating the results. The specific steps and tools used may vary depending on the requirements of the project or organization performing the record linkage.
The purpose of beyond probabilistic record linkage is to improve the accuracy, efficiency, and completeness of record linkage processes. By utilizing advanced techniques and approaches, it becomes possible to establish connections between records that may have been missed or incorrectly matched using traditional probabilistic methods. This can have a wide range of applications in fields such as healthcare, research, fraud detection, and data integration.
The specific information that needs to be reported on beyond probabilistic record linkage depends on the context and requirements of the project or organization. However, it generally includes details about the datasets being linked, the methodology used for record linkage, any data preprocessing or cleaning steps performed, and the results or outcomes of the linkage process. Additionally, any privacy, security, or ethical considerations related to the data linkage should also be documented and reported.
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