As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …

Knowledge graphs (KGs) represent facts in the form of nodes and relationships and are
widely used to represent and share knowledge in many different domains. However, their …

Error detection is the process of identifying problematic data cells that are different from their
ground truth. Functional dependencies (FDs) have been widely studied in support of this …

With data lakes and schema-free NoSQL document stores, extracting a descriptive schema
from JSON data collections is an acute challenge. In this paper, we target the discovery of …

Inclusion dependencies (INDs) demand that the value set that appears in one attribute is
contained in the value set that appears in a different attribute. The automatic discovery of …

Inclusion dependency is a relation between attributes of tables that indicates possible
Primary Key-Foreign Key references. Automatic discovery of inclusion dependencies is a …

Knowledge graph completion (aka~ link prediction), ie,~ the task of inferring missing
information from knowledge graphs, is a widely used task in many applications, such as …

Data dependencies are a key concept in data management and have been researched in
data integration, data quality and query optimization. With the increasing use of graph …

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 …

Data dependencies, such as functional dependencies (FDs), have been long recognized as
integrity constraints in databases [42]. They are firstly utilized in database design [3] …