ACM Transactions on Database Systems (TODS)
Integration of weighted knowledge bases
Artificial Intelligence
Reasoning About Data Provided By Federated Deductive Databases
Journal of Intelligent Information Systems
Combining Multiple Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Merging with Integrity Constraints
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Proving theorems in a multi-source environment
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Distribution of goals addressed to a group of agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Answering Queries Addressed to Several Databases According to a Majority Merging Approach
Journal of Intelligent Information Systems
| Hi-index | 0.00 |
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 ofan 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.