【目的/意義】利用數據挖掘技術分析涉恐人員的物流、資金流、信息流等數據進行反恐預警可以有效提高反恐工作效率和優化資源配置。【方法/過程】本文將研究如何利用信息增益決策樹對涉恐情報信息進行快速分類。分類過程為從根節點的涉恐人員屬性開始不斷產生新的分支。產生每個分支都需要計算不同屬性的信息增益并選擇分裂屬性。【結果/結論】文中的方法可以對大量涉恐情報基礎數據進行快速分類,在實際工作中可以與關聯分析、聚類分析、異常檢測等其他數據挖掘方法組合使用。該方法既可以應用于公安情報學專業本科生的課堂教學,也可以應用于情報分析人員的培訓。

【Purpose/significance】Data mining technology becomes one of the common counter-terrorism methods that can be used to analyze the various daily lives of terrorists, such as logistics, the flow of money, the flow of information, etc.【Method/process】This paper will propose how to use decision tree of information gain to classify the information of terrorists quickly. The classification begins from the attribute of root and continue to generate new branches. Every branch selects forked attribute by comparing the information gains of different attributes.【Result/conclusion】Through combining with other data mining methods, decision tree of information gain will increase efficiency of intelligence analysis and improve the mechanism of terror threat warning. This method can be used not only in the undergraduate education, but also in training intelligence analysis.