Abstract
The World Wide Web can be viewed as a gigantic distributed database including millions of interconnected hosts some of which publish information via web servers or peer-to-peer systems. We present here a novel method for the extraction of semantically rich information from the web in a fully automated fashion. We illustrate our approach via a proof-of-concept application which scrutinizes millions of web pages looking for clues as to the trend of the Chinese stock market. We present the outcomes of a 210-day long study which indicates a strong correlation between the information retrieved by our prototype and the actual market behavior. © Springer-Verlag Berlin Heidelberg 2005.