Keys for graphs incorporate the topology and value constraints needed to uniquely identify
entities in a graph. They have been studied to support object identification, knowledge …

Linked data aims at publishing data expressed in RDF (Resource Description Framework) at
the scale of the worldwide web. These datasets interoperate by publishing links which …

Advances in information extraction have enabled the automatic construction of large
knowledge graphs (KGs) like DBpedia, Freebase, YAGO and Wikidata. Learning rules from …

Establishing identity links across RDF datasets is a central and challenging task on the way
to realising the Data Web project. It is well-known that data supplied by different sources can …

Instance matching (IM) is the process of matching instances across Knowledge Bases (KBs)
that refer to the same real‐world object (eg, the same person in two different KBs). Several …

Automatic approaches to key discovery on RDF datasets generate sets of discriminative
properties that can be used to configure data linking systems relying on link specifications …

Property Graph databases are being increasingly used within the industry as a powerful and
flexible way to model real-world scenarios. With this flexibility, a great challenge appears …

Keys for graphs uses the topology and value constraints needed to uniquely identify entities
in a graph database. They have been studied to support object identification, knowledge …

This paper introduces a constraint-based approach to clarify missing values in graphs. Our
method capitalizes on a set Σ of graph data constraints. An explanation is a sequence of …

Keys for graphs are a class of data quality rules that use topological and value constraints to
uniquely identify entities in a data graph. They have been studied to support object …