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Big Data Matching Using the Identity Correlation Approach

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Big Data Matching Using the Identity Correlation Approach

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Smyth, M.; Mccormack, K. (2016). Big Data Matching Using the Identity Correlation Approach. En CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics. Editorial Universitat Politècnica de València. 46-55. doi:10.4995/CARMA2016.2015.2991.

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/84779

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Title: Big Data Matching Using the Identity Correlation Approach
Author:
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Abstract:
[EN] The Identity Correlation Approach (ICA) is a statistical technique developed for matching big data where a unique identifier does not exist. This technique was developed to match the Irish Census 2011 dataset to Central ...[+]
Subjects: web data , internet data , big data , qca , pls , sem , conference
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
ISBN: 9788490484623
Source:
CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics.
DOI: 10.4995/CARMA2016.2015.2991
Publisher:
Editorial Universitat Politècnica de València
Publisher version: http://ocs.editorial.upv.es/index.php/CARMA/CARMA2016/paper/view/2991
Conference name: CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics
Conference place: Valencia, Spain
Conference date: July 06-07,2016
Type: Capítulo de libro Comunicación en congreso

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