The logic of knowledge bases
Combining Multiple Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Arbitration (or How to Merge Knowledge Bases)
IEEE Transactions on Knowledge and Data Engineering
Towards mathematical morpho-logics
Technologies for constructing intelligent systems
Artificial Intelligence - Special issue on nonmonotonic reasoning
Merging operators: Beyond the finite case
Information Fusion
Quota and Gmin merging operators
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
The Knowledge Engineering Review
Solving conflicts in information merging by a flexible interpretation of atomic propositions
Artificial Intelligence
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Generalizing conjunctive queries for informative answers
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
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The area of knowledge merging is concerned with merging conflicting information while preserving as much as possible. Most proposals in the literature work with knowledge bases expressed in propositional logic. We propose a new framework for merging knowledge bases expressed in (subsets of) first-order logic. Dilation operators (a concept originally introduced by Bloch and Lang) are employed and developed, and by combining them with the concept of comparison orderings we obtain a framework that is driven by model-based intuitions but that can be implemented in a syntax-based manner. We demonstrate specific dilation operators and comparison orderings for use in applications. We also show how postulates from the literature on knowledge merging translate into our framework and provide the conditions that dilation operators and comparison orderings must satisfy in order for the respective merging operators to satisfy the new postulates.