Author:
Chantaranimi Kittayaporn,Natwichai Juggapong
Publisher
Springer Nature Switzerland
Reference19 articles.
1. Azzalini, F., Jin, S., Renzi, M., Tanca, L.: Blocking techniques for entity linkage: a semantics-based approach. Data Sci. Eng. 6, 20–38 (2020). https://api.semanticscholar.org/CorpusID:228826450
2. Barlaug, N., Gulla, J.A.: Neural networks for entity matching: a survey. ACM Trans. Knowl. Discov. Data 15(3), 1–37 (2021)
3. Baxter, R.A., Christen, P., Churches, T.: A comparison of fast blocking methods for record linkage. In: Knowledge Discovery and Data Mining (2003). https://api.semanticscholar.org/CorpusID:522380
4. Campbell, S.R., Resnick, D.M., Cox, C.S., Mirel, L.B.: Using supervised machine learning to identify efficient blocking schemes for record linkage. Stat. J. IAOS 37(2), 673–680 (2021). https://doi.org/10.3233/sji-200779
5. Christen, P.: Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection. Springer Publishing Company, Berlin, Heidelberg (2012). Incorporated. https://doi.org/10.1007/978-3-642-31164-2