Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

A knowledge graph (KG), a special form of semantic network, integrates fragmentary data
into a graph to support knowledge processing and reasoning. KG quality control is important …

The quality of a Knowledge Graph (also known as Linked Data) is an important aspect to
indicate its fitness for use in an application. Several quality dimensions are identified, such …

In recent times, a multitude of knowledge-based applications draw knowledge from diverse
sources to cater to escalating task demands. However, the presence of errors or …

Content gaps in knowledge graphs impact downstream applications. Semantic Web
researchers have studied them mainly in relation to data quality or ontology evaluation, for …

Wikidata and Wikipedia have been proven useful for reason-ing in natural language
applications, like question answering or entitylinking. Yet, no existing work has studied the …

Urgent global research demands real-time dissemination of precise data. Wikidata, a
collaborative and openly licensed knowledge graph available in RDF format, provides an …

Data Bias Management Page 1 increase fairness across groups when doing data
augmentation,17 feature augmentation,5 or adjusting the metrics that measure bias.All these …

Wikidata is rapidly emerging as a key resource for a multitude of online tasks such as
Speech Recognition, Entity Linking, Question Answering, or Semantic Search. The value of …

General-purpose knowledge bases (KBs) are a cornerstone of knowledge-centric AI. Many
of them are constructed pragmatically from web sources and are thus far from complete. This …