Scanning World Wide Web Documents with the Vector Space Model

Authors

• Cheryl L. Aasheim, Georgia Southern UniversityFollow
• Gary J. Koehler, University of FloridaFollow

Document Type

Article

Publication Date

2006

Publication Title

Decision Support Systems

DOI

10.1016/j.dss.2005.03.002

ISSN

0167-9236

Abstract

The vector space model used in Information Retrieval is combined with discriminant analysis to provide an automated WWW environment scanning system to detect signals of interest to an organization. The vector space model converts text-based information to numerical vectors that are then used in discriminant analysis. We illustrate the methodology using news articles pertaining to a predefined randomly selected set of stocks to test whether they provide predictive signals on whether the stock's return will increase or decrease relative to the market in the target period following the report or whether the stock's trading volume will increase or decrease.

Comments

Copyright belongs to Elsevier. Information regarding the dissemination and usage of journal articles can be accessed through the following links.

• Open access licenses

• Article Sharing

• Journal Embargo Period List

Recommended Citation

Aasheim, Cheryl L., Gary J. Koehler. 2006. "Scanning World Wide Web Documents with the Vector Space Model." Decision Support Systems, 42 (2): 690-699: Association for Computing Machinery. doi: 10.1016/j.dss.2005.03.002 source: 10.1016/j.dss.2005.03.002
https://digitalcommons.georgiasouthern.edu/information-tech-facpubs/131

Copyright

See the publisher's copyright and reuse policies.