2015/07/07 by Dario Colazzo, Colazzo, Dario, Carlo Sartiani +1
Computer Science · #Advanced Database Systems and Queries #Artificial intelligence #Computer science #Data Management and Algorithms #Databases (cs.DB) #FOS: Computer and information sciences #Graph Theory and Algorithms #Inference #Information retrieval #Path expression #Programming Languages (cs.PL) #Programming language #Query expansion #Query language #Query optimization #RDF query language #Schema (genetic algorithms) #Search engine #Theoretical computer science #Type inference #Web query classification #Web search query #cs.DB #cs.PL
paper · pdf · open access · doi:10.48550/arxiv.1507.01708
published in arXiv (Cornell University) (Cornell University)
arxiv created 2015/07/07 · openalex publication_date 2015/07/07 · arxiv updated 2015/07/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Regular path query languages for data graphs are essentially untyped. The lack of type information greatly limits the optimization opportunities for query engines and makes application development more complex. In this paper we discuss a simple, yet expressive, schema language for edge-labelled data graphs. This schema language is, then, used to define a query type inference approach with good precision properties.