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Ontology-based entity matching in attributed graphs
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 …
entities in a graph. They have been studied to support object identification, knowledge …
FASTAGEDS: fast approximate graph entity dependency discovery
This paper studies the discovery of approximate rules in property graphs. First, we propose a
semantically meaningful measure of error for mining graph entity dependencies (GEDs) that …
semantically meaningful measure of error for mining graph entity dependencies (GEDs) that …
[HTML][HTML] An efficient approach for discovering graph entity dependencies (GEDs)
Graph entity dependencies (GEDs) are novel graph constraints, unifying keys and functional
dependencies, for property graphs. They have been found useful in many real-world data …
dependencies, for property graphs. They have been found useful in many real-world data …
Discovery of temporal graph functional dependencies
Temporal Graph Functional Dependencies (TGFDs) are a class of data quality rules
imposing topological, attribute dependency constraints over a period of time. To make …
imposing topological, attribute dependency constraints over a period of time. To make …
Discovery of keys for graphs [extended version]
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 …
in a graph database. They have been studied to support object identification, knowledge …
Keys as features for graph entity matching
Keys for graphs aim to uniquely identify entities represented by vertices in a graph, using the
combination of topological constraints and value equality constraints. This paper proposes …
combination of topological constraints and value equality constraints. This paper proposes …
Inconsistency detection with temporal graph functional dependencies
Data dependencies have been extended to graphs to characterize topological and value
constraints. Existing data dependencies are defined to capture inconsistencies in static …
constraints. Existing data dependencies are defined to capture inconsistencies in static …
Temporal dependencies for graphs
Graphs are increasingly being used to model information about entities, their properties, and
relationships between entities. Examples include relationships between customers, their …
relationships between entities. Examples include relationships between customers, their …
Mining Keys for Graphs
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 …
uniquely identify entities in a data graph. They have been studied to support object …
Efficient anomaly detection in property graphs
Property graphs are becoming increasingly popular for modeling entities, their relationships,
and properties. Due to the computational complexity, users are seldom to build complex …
and properties. Due to the computational complexity, users are seldom to build complex …