Mining the change of event trends for decision support in environmental scanning

Duen-Ren Liu*, Meng Jung Shih, Churn Jung Liau, Chin Hui Lai

*Corresponding author for this work

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

As the business environment has become increasingly complex, the demand for environmental scanning to assist company managers plan strategies and responses has grown significantly. The conventional technique for supporting environmental scanning is event detection from text documents such as news stories. Event detection methods recognize events, but neglect to discover the changes brought about by the events. In this work, we propose an event change detection (ECD) approach that combines association rule mining and change mining techniques. The approach detects changes caused by events to help managers respond rapidly to changes in the external environment. Association rule mining is used to discover event trends (the subject patterns of events) from news stories. The changes can be identified by comparing event trends in different time periods. The empirical evaluation showed that the discovered event changes can support decision-makers by providing up-to-date information about the business environment, which enables them to make appropriate decisions. The proposed approach is practical for business managers to be aware of environmental changes and adjust their business strategies accordingly.

Original languageEnglish
Pages (from-to)972-984
Number of pages13
JournalExpert Systems with Applications
Volume36
Issue number2 PART 1
DOIs
StatePublished - 1 Jan 2009

Keywords

  • Association rule mining
  • Change mining
  • Environmental scanning
  • Event detection
  • Event tracking
  • Information processing and management

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