Abstract
Data fusion is the process of merging records from multiple sources which represent the same real-world object into a single representation. This review of the literature concerns Data Fusion in the context of data integration, i.e., the integration of structured and semi-structured data from the same domain, and provides an overview of this field of research. We present why data fusion is becoming increasingly necessary, what it is used for (What for?), what methods and solutions for data fusion have been proposed in the literature (In what form?), what research challenges are still open in the data fusion area and what future research directions could usefully take (What is next?)
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This research was partially funded by INES 2.0, FACEPE grants APQ-0399-1.03/17 and APQ-0399-1.03/17, CAPES grant 88887.136410/2017-00, and CNPq grant 465614/2014-0.
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Canalle, G.K., Salgado, A.C. & Loscio, B.F. A survey on data fusion: what for? in what form? what is next?. J Intell Inf Syst 57, 25–50 (2021). https://doi.org/10.1007/s10844-020-00627-4
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DOI: https://doi.org/10.1007/s10844-020-00627-4