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Abstract: The problem of merging multiple databases of information about common entities is frequently encountered in KDD and decision support applications in large commercial and government organizations. The problem we study is often called the Merge/Purge problem and is difficult to solve both in scale and accuracy. Large repositories of data typically have numerous duplicate information entries about the same entities that are difficult to cull together without an intelligent "equational theory" that ... (Update)
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BibTeX entry: (Update)
M. A. Hernandez and S. J. Stolfo. Real-world data is dirty: Data Cleansing and the Merge/Purge problem. Journal of Data Mining and Knowledge Discovery, 2(1):9-37, 1998. http://citeseer.ist.psu.edu/hernandez98realworld.html More
@article{ hernandez98realworld,
author = "Mauricio A. Hernandez and Salvatore J. Stolfo",
title = "Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem",
journal = "Data Mining and Knowledge Discovery",
volume = "2",
number = "1",
pages = "9-37",
year = "1998",
url = "citeseer.ist.psu.edu/hernandez98realworld.html" }
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