Answering Queries Addressed to Several Databases According to a Majority Merging Approach
Purchase on Springer.com
$39.95 / €34.95 / £29.95*
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.
The general context of this work is the problem of merging data provided by several sources which can be contradictory. Focusing on the case when the information sources do not contain any disjunction, this paper first defines a propositional modal logic for reasoning with data obtained by merging several information sources according to a majority approach. Then it defines a theorem prover to automatically deduce these merged data. Finally, it shows how to use this prover to implement a query evaluator which answers queries addressed to several databases. This evaluator is such that the answer to a query is the one that could be computed by a classical evaluator if the query was addressed to the merged databases. The databases we consider are made of an extensional part, i.e. a set of positive or negative ground literals, and an intensional part i.e. a set of first order function-free clauses. A restriction is imposed to these databases in order to avoid disjunctive data.
- Baral, C., Kraus, S., Minker, J., and Subrahmanian, V.S. (1991). Combining Multiple Knowledge Bases. IEEE Trans. on Knowledge and Data Engineering, 3(2).
- Baral, C., Kraus, S., Minker, J., and Subrahmanian, V.S. (1992). Combining Knowledge Bases Consisting of First Order Theories. Computational Intelligence, 8(1).
- Cholvy, L. and Garion, Ch. (2001). A Logic to Reason an Contradictory Beliefs with a Majority Approach. In Proceedings of the IJCAI'01 Workshop: Inconsistencies in Data and Knowledge. Seattle.
- Cholvy, L. and Garion, Ch. (2002). Answering Queries Addressed to Merged Databases: A Query Evaluator which Implements a Majority Approach. In Proceedings of the 13th International Symposium on Methodologies for Intelligent Systems. Lyon, France.
- Chellas, B.F. (1980). Modal Logic, an Introduction. Cambridge University Press.
- Cholvy, L. (1993). Proving Theorems in a Multi-Sources Environment. In Proceedings of IJCAI'93 (pp. 66-71). Chambéry, France.
- Cholvy, L. (1998a). Reasoning About Merged Information. In Handbook of Defeasible Reasoning and Uncertainty Management, vol. 1. Kluwer Academic Publishers.
- Cholvy, L. (1998b). Reasoning with Data Provided by Federated Databases. Journal of Intelligent Information Systems, 10(1).
- Konieczny, S. and Pino-Pérez, R. (1998). On the Logic of Merging. In Proceedings of KR'98 (pp. 488-498). Trento.
- Konieczny, S. and Pino-Pérez, R. (1999). Merging with Integrity Constraints. In Proceedings of the Fifth European Conference on Symbolic and SQuantitative Appoaches to Reasoning with Uncertainty(ESCQARU'99), vol. 1638 of Lecture Notes in Artificial Intelligence (pp. 233-244). Springer-Verlag.
- Liau, C. (2000). A Conservative Approach to Distributed Belief Fusion. In Proceedings of 3rd International Conference on Information Fusion (FUSION).
- Lin, J. (1996). Integration of Weighted Knowledge Bases. Artificial Intelligence, 83, 363-378.
- Lin, J. and Mendelzon, A.O. (1998). Merging Databases Under Constraints. International Journal of Cooperative Information Systems, 7(1).
- Benferhat, S., Dubois, D., Lang, J., Prade, H., Saffiotti, A., and Smets, P. (1998). A General Approach for Inconsistency Handling and Merging Information in Prioritized Knowledge Bases. In Proc. of KR'98, Trento.
- Subrahmanian, V.S. (1994). Amalgamating Knowledge Bases. ACM Transactions on Database Systems, 19(2), 291-331.
- Answering Queries Addressed to Several Databases According to a Majority Merging Approach
Journal of Intelligent Information Systems
Volume 22, Issue 2 , pp 175-201
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- database merging
- majority merging
- deductive databases
- Industry Sectors