Atyimo - Record Linkage Application for Heterogeneous Platforms
Authors
Robespierre Pita and Clicia Pinto and Marcos Barreto and Spiros Denaxas
- FEDERAL UNIVERSITY OF BAHIA (UFBA), ATYIMOLAB (www.atyimolab.ufba.br)
- University College London, Denaxas Lab (www.denaxaslab.org)
More information
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Pita R., Mendonça E., Reis S., Barreto M., Denaxas S. (2017) A Machine Learning Trainable Model to Assess the Accuracy of Probabilistic Record Linkage. In: Bellatreche L., Chakravarthy S. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2017. Lecture Notes in Computer Science, vol 10440. Springer.
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PITA, Robespierre; PINTO, Clicia; MELO, Pedro; Silva, Malu; BARRETO, Marcos; RASELLA, Davide. (2015) A Spark-based workflow for probabilistic record linkage of healthcare data. Workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR - EDBT/ICDT 2015), Brussels.
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PINTO, Clicia; PITA, Robespierre; BARBOSA, George; ARAÚJO, Bruno; BERTOLDO, Juracy; SENA, Samila; REIS, Sandra; FIACCONE, Rosemeire; AMORIM, Leila; ICHIHARA, Maria Yuri; BARRETO, Mauricio; BARRETO, Marcos; DENAXAS, Spiros. Probabilistic integration of large Brazilian socioeconomic and clinical databases. 30th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2017), Thessaloniki, 2017.
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PINTO, Clicia; BORATTO, Murilo; ALONSO, Pedro; BARRETO, Marcos. Scaling probabilistic record linkage on multicore and multi-GPU system. 17th International Conference on Computational and Mathematical Methods in Science and Engineering (CMMSE 2017), Cadiz, 2017