Intelligent financial news digest system

Liu, James N.K., Dai, Honghua and Zhou, Lina 2005, Intelligent financial news digest system, Lecture notes in computer science, vol. 3683, pp. 112-120.

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Title Intelligent financial news digest system
Author(s) Liu, James N.K.
Dai, Honghua
Zhou, Lina
Journal name Lecture notes in computer science
Volume number 3683
Start page 112
End page 120
Publisher Springer Berlin
Place of publication Berlin, Germany
Publication date 2005
ISSN 0302-9743
1611-3349
Summary We present an agent-based system Intelligent Financial News Digest System (IFNDS) for analyzing online financial news articles and associated material. The system can abstract, synthesize, digest, and classify the contents, and assesses whether the report is favorable to any company discussed in the reports. It integrates artificial intelligence technologies including traditional information retrieval and extraction techniques for the news analysis. It makes use of keyword statistics and backpropagation training data to identify companies named in reportage whether it is, evaluatively speaking, positive, negative or neutral. The system would be of use to media such as clipping services, media management, advertising, public relations, public interest, and e-commerce professionals and government non-governmental bodies interested in monitoring the media profiles of corporations, products, and issues.
Language eng
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2005, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008899

Document type: Journal Article
Collection: School of Information Technology
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