This paper is a survey of the research topics in the field of Semantic Web, Linked Data and
Web of Data. This study looks at the contributions of this research community over its first …

Domain-specific knowledge graphs have emerged as a field unto their own, steadily and
perhaps not so slowly. Graphs have been pervasive in AI for a long period of time, dating …

Links build the backbone of the Linked Data Cloud. With the steady growth in size of
datasets comes an increased need for end users to know which frameworks to use for …

Abstract With Linked Data, a very pragmatic approach towards achieving the vision of the
Semantic Web has gained some traction in the last years. The term Linked Data refers to a …

A central problem in the context of the Web of Linked Data as well as in data integration in
general is to identify entities in different data sources that describe the same real-world …

Semi-supervised learning targets the common situation where labeled data are scarce but
unlabeled data are abundant. It uses unlabeled data to help supervised learning tasks. In …

A significant portion of the evolution of Linked Data datasets lies in updating the links to
other datasets. An important challenge when aiming to update these links automatically …

Building and publishing knowledge graphs (KG) as Linked Data, either on the Web or in
private companies, has become a relevant and crucial process in many domains. This …

Links are important for the publication of RDF data on the web. Yet, establishing links
between data sets is not an easy task. We develop an approach for that purpose which …

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 …