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Author Zhou, Yinle ♦ Nelson, Eric ♦ Kobayashi, Fumiko ♦ Talburt, John R.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Entity resolution ♦ Corporate house-holding ♦ Data quality ♦ Graduate-level ER course ♦ Information quality ♦ Measurement ♦ Record linkage
Abstract This article discusses the topics, approaches, and lessons learned in teaching a graduate-level course covering entity resolution (ER) and its relationship to information quality (IQ). The course surveys a broad spectrum of ER topics and activities including entity reference extraction, entity reference preparation, entity reference resolution techniques, entity identity management, and entity relationship analysis. The course content also attempts to balance aspects of ER theory with practical application through a series of laboratory exercises coordinated with the lecture topics. As an additional teaching aid, a configurable, open-source entity resolution engine (OYSTER) was developed that allows students to experience with different types of ER architectures including merge-purge, record linking, identity resolution, and identity capture.
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-03-01
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 4
Issue Number 2
Page Count 10
Starting Page 1
Ending Page 10


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Source: ACM Digital Library