Title: An intelligent agent-based system for multilingual financial news digest

Authors: James N.K. Liu, M.K. Ho

Addresses: Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. ' Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

Abstract: Online financial news from different sources is widely available on the internet. There are systems available to help investors extract and analyse the financial news from these sources but many of these systems present news articles without categorisation and do not provide enough query options to accurately yet comprehensively search for news. In this paper, we extend our previous work to develop an intelligent agent-based system for multilingual news extraction. We adopt a document categorisation approach based on fuzzy keyword classification. The system applies fuzzy clustering to obtain a classification of keywords by concepts of the category. A category profile is developed and used as a search interface for document browsing. Experimental results show that the proposed categorise news agent is capable of categorising news documents with a reasonable rate of accuracy and the grouping news agent is able to assemble news groups of similar contents to facilitate information retrieval.

Keywords: intelligent agents; multilingual news extraction; document categorisation; fuzzy classification; agent-based systems; multi-agent systems; MAS; financial news digest; online financial news; internet; keyword classification; information retrieval; fuzzy clustering; category profiles; search interface; document browsing.

DOI: 10.1504/IJIIDS.2010.035580

International Journal of Intelligent Information and Database Systems, 2010 Vol.4 No.4, pp.337 - 354

Accepted: 04 Apr 2010
Published online: 30 Sep 2010 *

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