Ontologies are often viewed as the answer to the need for interoperable semantics in
modern information systems. The explosion of textual information on the Read/Write Web …

The explosive growth of textual data on the web coupled with the increase on demand for
ontologies to promote the semantic web, have made the automatic ontology construction …

The Wikipedia category graph serves as the taxonomic backbone for large-scale knowledge
graphs like YAGO or Probase, and has been used extensively for tasks like entity …

The entity type information in Knowledge Graphs (KGs) such as DBpedia, Freebase, etc. is
often incomplete due to automated generation. Entity Ty** is the task of assigning or …

Abstract The goal of Ontology Learning from Text is to learn ontologies that represent
domains or applications that change often. Manually learning and updating such ontologies …

In this paper, we present an automated method for taxonomy learning, focusing on concept
formation and hierarchical relation learning. To infer such relations, we partition the …

Knowledge Graphs (KGs) have recently gained attention for representing knowledge about
a particular domain. Since its advent, the Linked Open Data (LOD) cloud has constantly …