IntelliClean: A Knowledge-Based Intelligent Data Cleaner (2000) [29 citations — 0 self]
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author = {Mong Li Lee and Tok Wang Ling and Wai Lup Low},
title = {IntelliClean: A Knowledge-Based Intelligent Data Cleaner},
booktitle = {In Knowledge Discovery and Data Mining},
year = {2000},
pages = {290--294}
}
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Abstract:
Existing data cleaning methods work on the basis of computing the degree of similarity between nearby records in a sorted database. High recall is achieved by accepting records with low degrees of similarity as duplicates, at the cost of lower precision. High precision is achieved analogously at the cost of lower recall. This is the recall-precision dilemma. In this paper, we propose a generic knowledge-based framework for effective data cleaning that implements existing cleaning strategies and more. We develop a new method to compute transitive closure under uncertainty which handles the merging of groups of inexact duplicate records. Experimental results show that this framework can identify duplicates and anomalies with high recall and precision.
Citations
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| 132 | CP: An efficient domain-independent algorithm for detecting approximately duplicate database records – AE, Elkan - 1997 |
| 37 | Rete: A fast algorithm for the many patterns/many objects match problem – Forgy - 1982 |
| 33 | the java expert system shell – Jess - 1997 |
| 16 | Cleansing Data for Mining and Warehousing – Lee, Lu, et al. - 1999 |
| 12 | Dealing with Dirty Data – Kimball - 1996 |
| 5 | Expert systems: Principles and programming (3rd edition – Giarratano, Riley - 1998 |
| 1 | Challenges of e#cient data cleansing – Maydanchik - 1999 |
| 1 | A comparison of two incremental merge/purge strategies – Waller - 1998 |
