Temporal Knowledge for Timely Intelligence

  • Gerhard Weikum
  • Srikanta Bedathur
  • Ralf Schenkel
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 84)


Knowledge bases about entities and their relationships are a great asset for business intelligence. Major advances in information extraction and the proliferation of knowledge-sharing communities like Wikipedia have enabled ways for the largely automated construction of rich knowledge bases. Such knowledge about entity-oriented facts can greatly improve the output quality and possibly also efficiency of processing business-relevant documents and event logs. This holds for information within the enterprise as well as in Web communities such as blogs.

However, no knowledge base will ever be fully complete and real-world knowledge is continuously changing: new facts supersede old facts, knowledge grows in various dimensions, and completely new classes, relation types, or knowledge structures will arise. This leads to a number of difficult research questions regarding temporal knowledge and the life-cycle of knowledge bases. This short paper outlines challenging issues and research opportunities, and provides references to technical literature.


Information Extraction Temporal Knowledge Candidate Entity Rich Knowledge Base Open Information Extraction 
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 2011

Authors and Affiliations

  • Gerhard Weikum
    • 1
  • Srikanta Bedathur
    • 1
  • Ralf Schenkel
    • 2
  1. 1.Max Planck Institute for InformaticsGermany
  2. 2.Saarland UniversitySaarbrueckenGermany

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