Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering the set of fundamental rule changes
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Subject Classification in the Oxford English Dictionary
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A System for new event detection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Event detection from online news documents for supporting environmental scanning
Decision Support Systems - Special issue: Knowledge management technique
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Detecting and tracking regional outliers in meteorological data
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Mining changes in customer behavior in retail marketing
Expert Systems with Applications: An International Journal
An efficient data mining approach for discovering interesting knowledge from customer transactions
Expert Systems with Applications: An International Journal
Post-analysis of learned rules
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Discovering competitive intelligence by mining changes in patent trends
Expert Systems with Applications: An International Journal
Locality sensitive hashing for sampling-based algorithms in association rule mining
Expert Systems with Applications: An International Journal
SoMEST: a model for detecting competitive intelligence from social media
Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments
Multi-perspective linking of news articles within a repository
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
| Hi-index | 12.05 |
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.