Accommodating imprecision in database systems

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Accommodating imprecision in database systems: issues and solutions

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ACM SIGMOD Record archive
Volume 19 , Issue 4 (December 1990) table of contents
Directions for future database research & development

Pages: 69 - 74

Year of Publication: 1990

ISSN:0163-5808

Author

Amihai Motro

Information Systems and Systems Engineering Department, George Mason University, Fairfax, VA

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 2, Downloads (12 Months): 14, Citation Count: 14

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ABSTRACT

Most database systems are designed under assumptions of precision of both the data stored in their databases, and the requests to retrieve data. In reality, however, these assumptions are often invalid, and in recent years considerable attention has been given to issues of imprecision in database systems. In this paper we review the major solutions for accommodating imprecision, and we describe issues that have yet to addressed, offering possible research directions.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY 14

	Ana Paula Ambrosio, Introducing semantics in conceptual schema reuse, Proceedings of the third international conference on Information and knowledge management, p.50-56, November 29-December 02, 1994, Gaithersburg, Maryland, United States
	O. Haase , A. Henrich, Error propagation in distributed databases, Proceedings of the fourth international conference on Information and knowledge management, p.387-394, November 29-December 02, 1995, Baltimore, Maryland, United States
	T. S. Jayram , Satyen Kale , Erik Vee, Efficient aggregation algorithms for probabilistic data, Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, p.346-355, January 07-09, 2007, New Orleans, Louisiana
	Doug Burdick , Prasad M. Deshpande , T. S. Jayram , Raghu Ramakrishnan , Shivakumar Vaithyanathan, OLAP over uncertain and imprecise data, The VLDB Journal — The International Journal on Very Large Data Bases, v.16 n.1, p.123-144, January 2007
	D. Dey , S. Sarkar, Generalized Normal Forms for Probabilistic Relational Data, IEEE Transactions on Knowledge and Data Engineering, v.14 n.3, p.485-497, May 2002
	Doug Burdick , Prasad M. Deshpande , T. S. Jayram , Raghu Ramakrishnan , Shivakumar Vaithyanathan, OLAP over uncertain and imprecise data, Proceedings of the 31st international conference on Very large data bases, August 30-September 02, 2005, Trondheim, Norway
	Arbee L. P. Chen , Jui-Shang Chiu , Frank S. C. Tseng, Evaluating Aggregate Operations Over Imprecise Data, IEEE Transactions on Knowledge and Data Engineering, v.8 n.2, p.273-284, April 1996
	Oliver Haase , Andreas Henrich, A Hybrid Representation of Vague Collections for Distributed Object Management Systems, IEEE Transactions on Knowledge and Data Engineering, v.12 n.3, p.448-467, May 2000
	Frank S. C. Tseng , Arbee L. P. Chen , Wei Pang Yang, Searching a minimal semantically-equivalent subset of a set of partial values, The VLDB Journal — The International Journal on Very Large Data Bases, v.2 n.4, p.489-512, October 1993
	Murat Koyuncu , Adnan Yazici, IFOOD: An Intelligent Fuzzy Object-Oriented Database Architecture, IEEE Transactions on Knowledge and Data Engineering, v.15 n.5, p.1137-1154, September 2003
	Norbert Fuhr , Thomas Rölleke, A probabilistic relational algebra for the integration of information retrieval and database systems, ACM Transactions on Information Systems (TOIS), v.15 n.1, p.32-66, Jan. 1997
	M. W. Bright , A. R. Hurson , S. Pakzad, Automated resolution of semantic heterogeneity in multidatabases, ACM Transactions on Database Systems (TODS), v.19 n.2, p.212-253, June 1994
	Vesper Owei, An intelligent approach to handling imperfect information in concept-based natural language queries, ACM Transactions on Information Systems (TOIS), v.20 n.3, p.291-328, July 2002
	Simon Parsons, Current Approaches to Handling Imperfect Information in Data and Knowledge Bases, IEEE Transactions on Knowledge and Data Engineering, v.8 n.3, p.353-372, June 1996