2026-09-20T07:55:26Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/18304 2023-07-10 col_2142_10761 col_2142_5131 com_2142_10755 com_2142_234 com_2142_5130

Chang, Kevin C-C. Gu, Randy S. 2011-01-14T22:45:32Z 2011-01-14T22:45:32Z 2011-01-14T22:45:32Z 2010-12 The growing dependence of society on enormous quantities of information stored electronically has led to a corresponding rise in errors in this information. The stored data can be critically important, necessitating new ways of correcting anomalous records. Current cleaning techniques are very domain-specific and hard to extend, hindering their use in some areas. This work proposes an extensible framework for data cleaning, allowing users to customize the cleaning to their specific requirements. It defines categories of common cleaning operations, allowing more robust support for user-implemented cleaning functions in these categories. The experimental results show that the proposed data cleaning framework is an effective approach to cleaning data for arbitrary domains. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2010-12-06T22:32:50Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Gu_Randy.pdf: 1018675 bytes, checksum: 99083517d8b9a0f46938d0a6b33c1284 (MD5) Made available in DSpace on 2011-01-14T22:45:32Z (GMT). No. of bitstreams: 2 Gu_Randy.pdf: 1019060 bytes, checksum: a6e102659d31da4775e3eb22ede8e1e4 (MD5) license.txt: 4058 bytes, checksum: 03e2936f9233e17d6665b7c37e1b14ed (MD5) http://hdl.handle.net/2142/18304 en Copyright 2010 Randy Siran Gu Data Cleaning Data Cleaning Framework: An Extensible Approach to Data Cleaning Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:CS:BS/MS Program - UIUC 10KS1854MS