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Source Conference on Information and Knowledge Management archive
Proceedings of the 14th ACM international conference on Information and knowledge management table of contents
Bremen, Germany
Pages: 3 - 3  
Year of Publication: 2005
ISBN:1-59593-140-6
Author
Thomas Hofmann  Darmstadt University of Technology, Darmstadt, Germany
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

Unstructured data is a valuable source of information and implicit knowledge. Yet, the bits and bytes of, e.g., text, image, or click-stream data need to be interpreted in order to transform them into business intelligence and actionable information. Clearly, this process needs to be automated to the largest possible extend in order to be scalable to the typical volumes of data. One way to accomplish this is through the use of machine learning and statistical modelling techniques. This talk will provide an overview of recent progress and new trends in machine learning and discuss their relevance for developing intelligent tools for search, information filtering, categorization, and knowledge extraction.