Summary of the paper

Title A Semantic Memory for Incremental Ontology Population
Authors Berenike Loos and Lasse Schwarten
Abstract Generally, ontology learning and population is applied as a semi-automatic approach to knowledge acquisition in natural language understanding systems. That means, after the ontology is created or populated, an expert of the domain can still change or refine the newly acquired knowledge. In an incremental ontology learning framework (as e.g. applied for open-domain dialog systems) this approach is not sufficient as knowledge about the real world is dynamic and, therefore, has to be acquired and updated constantly. In this paper we propose the storing of newly acquired instances of an ontological concept in a separate database instead of integrating them directly into the system’s knowledge base. The advantage is that possibly incorrect knowledge is not part of the system’s ontology but stored aside. Furthermore, information about the confidence about the learned instances can be displayed and used for a final revision as well as a further automatic acquisition.
Language Language-independent
Topics Knowledge representation, Lexicon, lexical database, Ontologies
Full paper A Semantic Memory for Incremental Ontology Population
Slides -
Bibtex @InProceedings{LOOS08.235,
  author = {Berenike Loos and Lasse Schwarten},
  title = {A Semantic Memory for Incremental Ontology Population},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  month = {may},
  date = {28-30},
  address = {Marrakech, Morocco},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-4-0},
  note = {},
  language = {english}

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