A Qualitative Literature Review on Linkage Techniques for Data Integration

Date
2020-01-07
Authors
Kruse, Felix
Hassan, Ahmad Pajam
Awick, Jan-Philipp
Marx Gómez, Jorge
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The data linkage techniques ”entity linking” and ”record linkage” get rising attention as they enable the integration of multiple data sources for data, web, and text mining approaches. This has resulted in the development of numerous algorithms and systems for these techniques in recent years. The goal of this publication is to provide an overview of these numerous data linkage techniques. Most papers deal with record linkage and structured data. Processing unstructured data through entity linking is rising attention with the trend Big Data. Currently, deep learning algorithms are being explored for both linkage techniques. Most publications focus their research on a single process step or the entire process of ”entity linking” or ”record linkage”. However, the papers have the limitation that the used approaches and techniques have always been optimized for only a few data sources.
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Data, Text, and Web Mining for Business Analytics, big data integration, data science, entity linking, linkage techniques, record linkage
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11 pages
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Related To
Proceedings of the 53rd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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