Using Social Media for Ontology Enrichment

  • Paola Monachesi
  • Thomas Markus
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6089)


In order to support informal learning, we complement the formal knowledge represented by ontologies developed by domain experts with the informal knowledge emerging from social tagging. To this end, we have developed an ontology enrichment pipeline that can automatically enrich a domain ontology using: data extracted by a crawler from social media applications, similarity measures, the DBpedia knowledge base, a disambiguation algorithm and several heuristics. The main goal is to provide dynamic and personalized domain ontologies that include the knowledge of the community of users.


Similarity Measure Cosine Similarity Domain Ontology Input Term Python Programming Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Paola Monachesi
    • 1
  • Thomas Markus
    • 1
  1. 1.Utrecht UniversityUtrechtThe Netherlands

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