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2005
Conference Paper
Titel

From bits and bytes to information and knowledge

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 modeling 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.
Author(s)
Hofmann, T.
Hauptwerk
14th ACM International Conference on Information and Knowledge Management 2005. Proceedings
Konferenz
International Conference on Information and Knowledge Management (CIKM) 2005
Thumbnail Image
DOI
10.1145/1099554.1099557
Language
English
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