Chapter 3: Search for Knowledge

  • Gerhard Weikum
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5950)


There are major trends to advance the functionality of search engines to a more expressive semantic level. This is enabled by the advent of knowledge-sharing communities such as Wikipedia and the progress in automatically extracting entities and relationships from semistructured as well as natural-language Web sources. In addition, Semantic-Web-style ontologies, structured Deep-Web sources, and Social-Web networks and tagging communities can contribute towards a grand vision of turning the Web into a comprehensive knowledge base that can be efficiently searched with high precision. This vision and position paper discusses opportunities and challenges along this research avenue. The technical issues to be looked into include knowledge harvesting to construct large knowledge bases, searching for knowledge in terms of entities and relationships, and ranking the results of such queries.


Query Processing Ranking Model Keyword Query Triple Pattern Entity Ranking 
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

  • Gerhard Weikum
    • 1
  1. 1.Max-Planck Institute for InformaticsSaarbrueckenGermany

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