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DATENSATZ AKTIONENEXPORT

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Konferenzbeitrag

Temporal Knowledge for Timely Intelligence

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44104

Bedathur,  Srikanta
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45380

Schenkel,  Ralf
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Zitation

Weikum, G., Bedathur, S., & Schenkel, R. (2011). Temporal Knowledge for Timely Intelligence. In M. Castellanos, U. Dayal, & V. Markl (Eds.), Enabling Real-Time Business Intelligence (pp. 1-6). Berlin: Springer. doi:10.1007/978-3-642-22970-1_1.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-14CA-2
Zusammenfassung
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.