WoLE 2012
Web of Linked Entities



Call for Papers

This workshop envisions the Semantic Web as a Web of Linked Entities (WoLE), which transparently connects the World Wide Web (WWW) and the Giant Global Graph (GGG) using methods from Information Retrieval (IR) and Natural Language Processing (NLP).

Submissions to the workshop should cover one of these topics:

  1. Improvements upon the state of the art in NLP using information in the Linked Open Data (LOD) cloud;
  2. Knowledge extraction from text and HTML documents (especially structured and semi-structured documents) on the Web, with a special focus on scalability, evaluation of precision & recall and/or live systems;
  3. Representation of NLP tool output and NLP resources as RDF/OWL and especially connections to linked data;
  4. Novel applications to search and browse the WWW with the help of extracted knowledge and the Web of Data.

Our goal is to bring together research and expertise from different communities such as Information Extraction, Natural Language Processing and Semantic Web. In particular, topics of interest include:

  • Text and web mining
  • Pattern and semantic analysis of natural language, reading the web, learning by reading
  • Large-scale information extraction
  • Usage mining
  • Entity resolution and automatic entities discovery
  • Frequent pattern analysis of entities
  • Entity linking, named entity disambiguation, cross-document co-reference resolution
  • Ontology representation of natural language text
  • Analysis of ontology models for natural language text
  • Learning and refinement of ontologies
  • Natural language taxonomies modeled to Semantic Web ontologies
  • Disambiguation through knowledge base
  • Multilingual entity recognition task of real world entities
  • Use cases of entity recognition for Linked Data applications
  • Relationship extraction, slot filling
  • Impact of entity linking on information retrieval, semantic search
  • Conversion of NLP tool output to RDF (NIF, Lemon, OLiA, NERD)
  • Usage of LOD data to improve perfomance of NLP processes
  • Semantification of Web pages such as blogs, forum, etc.