Information Extraction in Finance (inbunden)
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Inbunden (Hardback)
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WIT Press
234 x 158 x 19 mm
453 g
Information Extraction in Finance (inbunden)

Information Extraction in Finance

Inbunden Engelska, 2008-09-30
Specialorder (osäker tillgång). Skickas inom 11-20 vardagar.
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This books analyses the state of the art of applied research in a challenging field: natural language understanding of financial news. Currently, thanks to the world-wide technological spreading, stock market traders are overwhelmed with financial information, both numerical and textual, which has to be analysed quickly in order to react before market conditions change again. While there are several well-known numerical techniques for quantitative data, textual information is usually manually examined investing a lot of precious human time. This book shows how information extraction can be successfully applied to this task, at the same time speeding up the process and freeing the trader from this workload. The book's main focus has therefore a double identity: finance, especially intra-day trading with large amounts of news arriving at a too fast pace to be examined manually, and information extraction, especially real-time analysis of predetermined events. Both sectors bring new problems and innovative techniques, which are overviewed through many examples.
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Övrig information

Since obtaining his Ph.D. in Artificial Intelligence in Finance from the University of Durham (UK) in 1997, Dr. Marco Costantino has been employed in the financial industry, first with J P Morgan and, since 2003, as Financial Markets Manager with the Royal Bank of Scotland. He is the author of numerous conference papers and journal articles on artificial intelligence in finance and multimedia and hypertext environments. Dr. Paolo Coletti teaches courses in Computer Science and Information Processing at the School of Economics and Management of the Free University of Bozen-Bolzano, Italy.


1: Financial information and investment decisions 2: Financial tools - Conventional quantitative tools; Artificial intelligence techniques; Qualitative tools 3: Traditional approaches on qualitative information - Reuters 3000 Xtra; Bloomberg; Other information systems; Weaknesses of traditional approaches 4: Natural language processing and information extraction - Information retrieval; The TREC competitions; Information extraction; The MUC competitions; The MUC systems; User-definable template interfaces; Conclusions 5: LOLITA and IE-expert systems - Introduction and scope; Architecture of the system; Information extraction; Templates available in the system; Implementation of the financial templates; The takeover financial template; Performance; Integration with elementised news systems; The IE-expert system 6: Conclusions