Entity reconciliation in big data sources: A systematic mapping study

作者：

Highlights：

• Systematic Mapping Study about entity reconciliation in Big Data.

• Eleven databases were consulted. Rigorous process where 2255 papers were analyzed leaving 61 primary studies.

• Analytic data statistics after the classification of the primary studies.

• Discussion that presents some interesting intelligent system-based papers for solving entity reconciliation and conclusions obtained from the data retrieved.

摘要

•Systematic Mapping Study about entity reconciliation in Big Data.•Eleven databases were consulted. Rigorous process where 2255 papers were analyzed leaving 61 primary studies.•Analytic data statistics after the classification of the primary studies.•Discussion that presents some interesting intelligent system-based papers for solving entity reconciliation and conclusions obtained from the data retrieved.

论文关键词：Systematic mapping study,Entity reconciliation,Heterogeneous databases,Big data

论文评审过程：Received 27 July 2016, Revised 2 March 2017, Accepted 3 March 2017, Available online 10 March 2017, Version of Record 11 April 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.03.010