本研究综合利用情报学、数据挖掘、人工智能、知识管理等多学科的理论与方法，从不同角度、不同层面研究跨区域网络情报智能分析，从而实现从海量信息中抽取可信情报知识，为政府决策提供参考的情报分析目标。研究的主要内容包括：（1）跨区域网络情报智能分析模型研究，以数据挖掘为基础，融合机器学习、本体论、人工智能等有关理论，在语义层面研究并构建面向东盟的跨区域情报的分类分析模型和多维情报智能分析模型，实现了包含信息采集、信息预处理、知识挖掘、情报分析等一体化情报分析流程；（2）跨区域情报智能分析方法研究。通过比较国内外情报分析方法，融合数据挖掘、语义分析、可视化分析等先进理论技术，深入探索和研究了旨在支持网络情报分析的方法：传统竞争情报分析与数据挖掘融合的方法、统计分析与语义分析结合的方法、可视化情报分析方法等；（3）主要模型与算法的实验研究，利用先期研究构建的数据集，对跨区域情报智能分析体系进行验证。

This project comprehensively uses the theories and methods of related disciplines, such as information science, data mining, artificial intelligence and knowledge management, studies the cross-region network intelligence analysis from different aspects and levels, achieves the goal to extract trusted intelligence from huge amounts of information and provide decision making for government. The main content of project include：(1) Intelligent analysis model for cross-region network intelligence. This model constructs an ASEAN-oriented integrated intelligent processing framework which contains classification analysis and multidimensional intelligence analysis. It can implement the functions of information collecting, information pre-processing, knowledge mining and intelligence analyzing. (2) The methods of cross-region intelligent analysis. Having compared the methods of intelligence analysis in and out of our country, combing the advanced technologies of data mining, semantic analysis and visualization, we explores the methods which support network intelligence analysis, such as the integration methods of traditional intelligence analysis and data mining, statistical analysis and semantic analysis, visual intelligence analysis. (3) Developing the main models and algorithms. Use the data sets which constructs at previous research to verify the cross-region intelligence analysis system.