Research and Application of the Data Mining Technology in Economic Intelligence System

Area of Science:

• Economic Intelligence Systems
• Data Mining Applications
• Information Management

Background:

• Modern economies rely heavily on timely information for enterprise decision-making.
• Extracting valuable enterprise information efficiently is a critical challenge.
• Economic intelligence systems are essential for leveraging data in business.

Purpose of the Study:

• To apply data mining techniques to enhance economic intelligence systems.
• To develop an economic intelligence information database and system.
• To analyze and mine interrelationships within economic data objects.

Main Methods:

• Information integration to obtain data object models.
• Data mining methods, including association rules and classification prediction.
• Development and implementation of an economic intelligence information database and system.
• Algorithm application for efficient and accurate information extraction.

Main Results:

• An economic intelligence system was developed and realized.
• The proposed data mining algorithm demonstrated improved performance.
• Classification accuracy was found to be 2.64% higher compared to the ID3 algorithm.

Conclusions:

• Data mining algorithms are effective for economic intelligence systems.
• The developed system provides a method for extracting crucial economic information.
• Enhanced classification accuracy supports better enterprise decision-making.