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17th International Conference on Database and Expert Systems Applications (DEXA'06)
Text Mining of Business News for Forecasting
Krakow, Poland
September 04-September 08
ISBN: 0-7695-2641-1
Petr Kroha, University of Technology, Germany
Ricardo Baeza-Yates, Universidad de Chile, Chile
Bjorn Krellner, University of Technology, Germany
In this paper, we analyze the relation between the content of business news and long-term market trends. We describe cleansing and classification of business news, we investigate how much similarity good news and bad news have, and how their ratio behaves in context of long-terms market trends. We have processed more than 400 thousand business news coming from the years 1999 to 2005. We present results of our experiments and their possible impact on forecasting of long-term market trends.
Citation:
Petr Kroha, Ricardo Baeza-Yates, Bjorn Krellner, "Text Mining of Business News for Forecasting," dexa, pp.171-175, 17th International Conference on Database and Expert Systems Applications (DEXA'06), 2006
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