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Information is extracted based on relation patterns that serve as queries. The results are then visualized to allow detailed market analysis. The current status of the reported work is that we are already implemented most of the required infrastructure (UIMA, Pronto, Omnifind) and started some of the outlined experiments. | Information is extracted based on relation patterns that serve as queries. The results are then visualized to allow detailed market analysis. The current status of the reported work is that we are already implemented most of the required infrastructure (UIMA, Pronto, Omnifind) and started some of the outlined experiments. | ||
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Version vom 15. August 2009, 19:10 Uhr
Iterative Learning of Relation Patterns for Market Analysis with UIMA
Iterative Learning of Relation Patterns for Market Analysis with UIMA
Published: 2007
April
Buchtitel: UIMA Workshop at GLDV Frühjahrstagung
Referierte Veröffentlichung
BibTeX
Kurzfassung
Monitoring news as well as corporate and community websites is a important task in market analysis. Yet, it requires
much manual processing and is inherently incomplete as only a small fraction of the data produced on the Web can be processed by human analysts. We present here our ongoing efforts to employ UIMA annotations and search on UIMA-annotated documents for supporting market analysis.
Information is extracted based on relation patterns that serve as queries. The results are then visualized to allow detailed market analysis. The current status of the reported work is that we are already implemented most of the required infrastructure (UIMA, Pronto, Omnifind) and started some of the outlined experiments.
Download: Media:2007_1472_Blohm_Iterative_Learn_1.pdf
Information Retrieval, Informationsextraktion