Quality Awareness over Graph Pattern Queries

Philippe Rigaux 1 Virginie Thion 2
1 CEDRIC - VERTIGO - CEDRIC. Bases de données avancées
CEDRIC - Centre d'études et de recherche en informatique et communications
2 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : We examine the problem of quality awareness when querying graph databases. According to quality annotations that denote quality problems appearing in data subgraphs (the annotations typically result from collaborative practices in the context of open data usage like e.g. users’ feedbacks), we propose a notion of quality aware (graph pattern) query based on (usage-dependent) quality profiles. In this paper, we present the formal foundations of the approach. We also show how to simply extend a generic state-of-the-art algorithm for graph pattern queries evaluation in order to implement quality awareness at evaluation time and we study its complexity. We then expose implementation guidelines, supported by a proof-of-concept prototype based on the Neo4J graph database management system.
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Philippe Rigaux, Virginie Thion. Quality Awareness over Graph Pattern Queries. Proceedings of the International Database Engineering & Applications Symposium (IDEAS), Jul 2017, Bristol, United Kingdom. ⟨hal-01528456⟩

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