2018/02/23 by Francesco Belardinelli, Belardinelli, Francesco, Umberto Grandi +1 · 1 citation
Computer Science · #Advanced Algebra and Logic #Bayesian Modeling and Causal Inference #Databases (cs.DB) #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #cs.DB
paper · pdf · doi:10.48550/arxiv.1802.08586
20 pages
arxiv created 2018/02/23 · openalex publication_date 2018/02/23 · arxiv updated 2018/02/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Knowledge can be represented compactly in a multitude ways, from a set of propositional formulas, to a Kripke model, to a database. In this paper we study the aggregation of information coming from multiple sources, each source submitting a database modelled as a first-order relational structure. In the presence of an integrity constraint, we identify classes of aggregators that respect it in the aggregated database, provided all individual databases satisfy it. We also characterise languages for first-order queries on which the answer to queries on the aggregated database coincides with the aggregation of the answers to the query obtained on each individual database. This contribution is meant to be a first step on the application of techniques from rational choice theory to knowledge representation in databases.