A Model-Based Approach to Updating Databases with Incomplete Information.
Marianne Winslett:
A Model-Based Approach to Updating Databases with Incomplete Information.
ACM Trans. Database Syst. 13(2): 167-196(1988)@article{DBLP:journals/tods/Winslett88,
author = {Marianne Winslett},
title = {A Model-Based Approach to Updating Databases with Incomplete
Information},
journal = {ACM Trans. Database Syst.},
volume = {13},
number = {2},
year = {1988},
pages = {167-196},
ee = {http://doi.acm.org/10.1145/42338.42386, db/journals/tods/Winslett88.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
Suppose one wishes to construct, use, and maintain a database
of facts about the real world, even though the state of that
world is only partially known. In the artificial intelligence
domain, this problem arises when an agent has a base set of
beliefs that reflect partial knowledge about the world, and
then tries to incorporate new, possibly contradictory knowledge
into this set of beliefs. In the database domain, one facet of
this situation is the well-known null values problem. We choose
to represent such a database as a logical theory, and view the
models of the theory as representing possible states of the
world that are consistent with all known information.
How can new information be incorporated into the database?
For example, given the new information that "b or c is true,"
how can one get rid of all outdated information about b and c,
add the new information, and yet in the process not disturb any
other information in the database? In current-day database
management systems, the difficult and tedious burden of
determining exactly what to add and remove from the database is
placed on the user. The goal of our research was to relieve
users of that burden, by equipping the database management
system with update algorithms that can automatically determine
what to add and remove from the database.
Under our approach, new information about the state of the
world is input to the database management system as a
well-formed formula that the state of the world is now known
to satisfy. We have constructed database update algorithms to
interpret this update formula and incorporate the new
information represented by the formula into the database
without further assistance from the user. In this paper we
show how to embed the incomplete database and the incoming
information in the language of mathematical logic, explain the
semantics of our update operators, and discuss the algorithms
that implement these operators.
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BibTeX
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Referenced by
- Julie Wilks:
Querying and Updating Constraint Databases with Incomplete Information.
ADBIS 1997: 80-89
- Jui-Shang Chiu, Arbee L. P. Chen:
An Exploration of Relationships Among Exclusive Disjunctive Data.
IEEE Trans. Knowl. Data Eng. 7(6): 928-940(1995)
- Dominique Laurent, Viet Phan Luong, Nicolas Spyratos:
Updating Intensional Predicates in Deductive Databases.
ICDE 1993: 14-21
- Anthony J. Bonner, Michael Kifer, Mariano P. Consens:
Database Programming in Transaction Logic.
DBPL 1993: 309-337
BibTeX
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