Active Learning Based Similarity Filtering for Efficient and Effective Record Linkage-Reference-Cited by-同舟云学术

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Active Learning Based Similarity Filtering for Efficient and Effective Record Linkage

Published:2021 Issue: Volume: Page:321-333
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
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Author:

Nanayakkara Charini,Christen Peter,Ranbaduge Thilina

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-75765-6_26

Reference24 articles.

1. Arasu, A., Götz, M., Kaushik, R.: On active learning of record matching packages. In: ACM SIGMOD. pp. 783–794. Indianapolis (2010)

2. Bhattacharya, I., Getoor, L.: Collective entity resolution in relational data. ACM TKDD 1(1), 5-es (2007)

3. Christen, P.: Data Matching - Concepts and Rechniques for Record Linkage, Entity Resolution, and Duplicate Detection. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31164-2

4. Christen, P., Ranbaduge, T., Schnell, R.: Linking Sensitive Data. Springer, Heidelberg (2020). https://doi.org/10.1007/978-3-030-59706-1

5. Dong, X.L., Srivastava, D.: Big Data Integration. Synthesis Lectures on Data Management, Morgan and Claypool Publishers, San Rafael (2015)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Locality Sensitive Hashing with Temporal and Spatial Constraints for Efficient Population Record Linkage;Proceedings of the 31st ACM International Conference on Information & Knowledge Management;2022-10-17

2. Decision Support System using Weighting Similarity Model for Constructing Ground-Truth Dataset;2022 9th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI);2022-10-06

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