Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
4-1993
Abstract
The objective of entity identification is to determine the correspondence between object instances from more than one database. Entity identification at the instance level, assuming that schema level heterogeneity has been resolved a priori, is examined. Soundness and completeness are defined as the desired properties of any entity identification technique. To achieve soundness, a set of identity and distinctness rules are established for entities in the integrated world. The use of extended key, which is the union of keys, and possibly other attributes, from the relations to be matched, and its corresponding identify rule are proposed to determine the equivalence between tuples from relations which may not share any common key. Instance level functional dependencies (ILFD), a form of semantic constraint information about the real-world entities, are used to derive the missing extended key attribute values of a tuple.
Keywords
ILFD, completeness, database integration, distinctness rules, entity identification, extended key, extended key attribute values, instance level, instance level functional dependencies, integrated world, object instances, real-world entities, schema level heterogeneity, semantic constraint information, tuple
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering
Publication
9th International Conference on Data Engineering: Proceedings: April 19-23, 1993, Vienna, Austria
First Page
294
Last Page
301
ISBN
9780818635700
Identifier
10.1109/ICDE.1993.344053
Publisher
IEEE Computer Society
City or Country
Los Alamitos, CA
Citation
LIM, Ee Peng; SRIVASTAVA, Jaideep; PRABHAKAR, Satya; and RICHARDSON, James.
Entity Identification in Database Integration. (1993). 9th International Conference on Data Engineering: Proceedings: April 19-23, 1993, Vienna, Austria. 294-301.
Available at: https://ink.library.smu.edu.sg/sis_research/925
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ICDE.1993.344053
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons