15 May 2015 Entity resolution using cloud computing
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Roles and capabilities of analysts are changing as the volume of data grows. Open-source content is abundant and users are becoming increasingly dependent on automated capabilities to sift and correlate information. Entity resolution is one such capability. It is an algorithm that links entities using an arbitrary number of criteria (e.g., identifiers, attributes) from multiple sources. This paper demonstrates a prototype capability, which identifies enriched attributes of individuals stored across multiple sources. Here, the system first completes its processing on a cloud-computing cluster. Then, in a data explorer role, the analyst evaluates whether automated results are correct and whether attribute enrichment improves knowledge discovery.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alex James, Alex James, Gregory Tauer, Gregory Tauer, Adam Czerniejewski, Adam Czerniejewski, Ryan M Brown, Ryan M Brown, Jesse Hartloff, Jesse Hartloff, Jillian Chaves, Jillian Chaves, Moises Sudit, Moises Sudit, } "Entity resolution using cloud computing", Proc. SPIE 9499, Next-Generation Analyst III, 94990S (15 May 2015); doi: 10.1117/12.2184178; https://doi.org/10.1117/12.2184178

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