Natural Language Processing


Natural Language Processing (NLP) is a key technology for the Semantic Web and important results such as entity linking, which enables the interoperability claim of the Semantic Web, are driven by NLP technologies. Similarly, in recent years the application of linked data technologies in the NLP and computational linguistics contexts, as exemplified by the growing linguistic linked open data cloud, has brought new tools to bear on tasks such as lexicography, under-resourced languages and research in the digital humanities. As such, we welcome papers that use ontologies and linked data technologies applied to NLP as well as NLP technologies applied to linked data and more in general to formal knowledge representation on the Semantic Web. We thus aim to further strengthen the interaction between these communities.



Topics include, but are not limited to:

  • Ontologies, terminology, wordnets and lexical resources
  • Information and knowledge extraction (including taxonomy extraction, ontology learning, knowledge graph learning)
  • Natural language understanding and the Semantic Web
  • Linguistic Frames and the Semantic Web
  • Data, information and knowledge integration across languages
  • Cross-lingual Ontology Alignment
  • Semantic text similarity
  • Linguistic Linked Data
  • Language data portals
  • Language data creation and management
  • Evaluation, provenance and visualization of linked data for NLP
  • Standards and interoperability of linked data for NLP
  • Linked data for under-resourced languages
  • Semantic search
  • Question answering
  • Natural language generation from structured knowledge graphs and ontologies
  • Text analytics for the Internet of Things
  • Applications of Linked Data in Digital Humanities, Social Sciences, and BioNLP

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