FIDS: an intelligent financial Web news articles digest system

Author

Lam, Wai ; Ho, Kei Shiu

Author_Institution

Dept. of Syst. Eng. & Eng. Manage., Chinese Univ. of Hong Kong, Shatin, China

Volume

31

Issue

6

fYear

2001

fDate

11/1/2001 12:00:00 AM

Firstpage

753

Lastpage

762

Abstract

In this paper, we present a system called FIDS (Financial Information Digest System), which can digest online financial news automatically. Compared to previous approaches, FIDS is unique in the way that it can understand news articles in different domains simultaneously. These domains are all concerned with financial news. The system is able to integrate the information from different articles by conducting automatic content-based classification and information item extraction. Moreover, it allows one to perform cross-validation on their contents. As a result, users can have access to more complete information which otherwise would be scattered in different articles

Keywords

abstracting; artificial intelligence; classification; financial data processing; full-text databases; information resources; natural languages; FIDS; Financial Information Digest System; automatic content-based classification; content cross-validation; information integration; information item extraction; intelligent financial Web news articles digest system; online financial news; simultaneous news article understanding; text summarization; Adaptive systems; Bayesian methods; Data mining; Explosions; Information filtering; Information filters; Internet; Learning systems; Scattering; Text categorization;

fLanguage

English

Journal_Title

Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Publisher

ieee

ISSN

1083-4427

Type

jour

DOI

10.1109/3468.983433

Filename

983433