Prediction of stock price movements based on concept map information

A. Soni, N.J.P. Eck, van, U. Kaymak

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

11 Citations (Scopus)
1 Downloads (Pure)


Visualization of textual data may reveal interesting properties regarding the information conveyed in a group of documents. In this paper, we study whether the structure revealed by a visualization method can be used as inputs for improved classifiers. In particular, we study whether the locations of news items on a concept map could be used as inputs for improving the prediction of stock price movements from the news. We propose a method based on information visualization and text classification for achieving this. We apply the proposed approach to the prediction of the stock price movements of companies within the oil and natural gas sector. In a case study, we show that our proposed approach performs better than a naive approach and a bag-of-words approach
Original languageEnglish
Title of host publicationIEEE Symposium on Computational Intelligence in Multicriteria Decision Making, 1-5 April 2007, Honolulu
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Print)1-4244-0702-8
Publication statusPublished - 2007


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