Entity Resolution (ER), a core task of Data Integration, detects different entity profiles that
correspond to the same real-world object. Due to its inherently quadratic complexity, a series …

Accessing and integrating human genomic data with phenotypes are important for
biomedical research. Making genomic data accessible for research purposes, however …

Entity resolution (ER) is a significant task in data integration, which aims to detect all entity
profiles that correspond to the same real-world entity. Due to its inherently quadratic …

Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of
the research examines ways for improving its effectiveness and time efficiency. The initial …

User facing topical web applications such as events or shopping sites rely on large
collections of data records about real world entities that are updated at varying latencies …

Record linkage is the process of matching records between two (or multiple) data sets that
represent the same real-world entity. An exhaustive record linkage process involves …

In the era of Big Data, integrating information from multiple sources has proven valuable in
various fields. To ensure a high-quality supply of multi-source data, repairing different types …

Entity Resolution (ER) is the process of identifying references referring to the same entity
from one or more data sources. In the ER process, most existing approaches exploit the …

The execution of data-intensive tasks such as entity matching on large data sources has
become a common demand in the era of Big Data. To face this challenge, cloud computing …

Linked Data describes an extensive set of structured but heterogeneous data sources where
entities are connected by formal semantic descriptions. In the vision of the Semantic Web …