Whether the goal is to estimate the number of people that live in a congressional district, to
estimate the number of individuals that have died in an armed conflict, or to disambiguate …

Blocking is a major task in entity matching. Numerous blocking solutions have been
developed, but as far as we can tell, blocking using the well-known tf/idf measure has …

Microservices has become a widely used and discussed architectural style for designing
modern applications due to advantages like granular scalability and maintainability …

Medical knowledge bases (KBs), distilled from biomedical literature and regulatory actions,
are expected to provide high-quality information to facilitate clinical decision making. Entity …

Entity matching (EM) finds data instances that refer to the same real-world entity. In 2015, we
started the Magellan project at UW-Madison, jointly with industrial partners, to build EM …

Abstract Knowledge graphs represented as RDF datasets are integral to many machine
learning applications. RDF is supported by a rich ecosystem of data management systems …

In this work, we use semantic knowledge sources, such as cross-domain knowledge graphs
(KGs) and domain-specific ontologies, to enrich structured data for various AI applications …

Entity matching is a crucial task in many real applications. Despite the substantial body of
research that focuses on improving the effectiveness of entity matching, enhancing its …

Efficiency techniques are an integral part of Entity Resolution, since its infancy. In this
survey, we organized the bulk of works in the field into Blocking, Filtering and hybrid …

Entity resolution (ER) is a core problem in data integration. Many companies have lots of
datasets where ER needs to be conducted to integrate the data. On the one hand, it is …