信息网络关联关系分析技术研究

项目名称： 信息网络关联关系分析技术研究

项目编号： No.61272137

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 李翠平

作者单位： 中国人民大学

项目金额： 80万元

中文摘要： 信息网络关联关系分析技术是国际上新兴的研究方向，其在实践中具有非常广泛的应用。目前信息网络关联关系分析技术在关系识别、关系抽取、静态的关系紧密度度量等方面，已经取得了许多有价值的研究成果。然而在面向新型网络的复杂关系分析方面仍然存在着诸多不足。网络的大规模、动态及异构特性，使得关联关系的表示、度量、预测、局部聚集及异常分析面临巨大挑战。因此，本项目拟深入研究大规模动态异构环境下的信息网络关联关系分析技术，拟提出基于控制集的关系概要生成方法、关系紧密度的非迭代计算方法和动态维护策略、综合不同类型关系影响的复合关系定义方法、基于通用线性模型的关系预测技术、面向混合概率模型的多类型关系协同聚簇技术、变化显著的连接子图的快速抽取机制、基于相对索引的子图相似性搜索方法等，解决关系的表示、度量、预测、异常及局部聚集性分析等问题，促进和推动信息网络关联关系分析技术的发展。

中文关键词： 信息网络；关联关系；关系预测；关系紧密度；局部聚集

英文摘要： Information networks are ubiquitous in many applications and association relationship analysis on such networks has attracted significant attention in the academic communities. In recent years, various approaches have been proposed to deal with a variety of association relationship related research problems, including relationship identification, relationship closeness measuring，relationship prediction，abnormal or local aggregated relationship analysis. However, the existing technologies can be infeasible and inefficient when, as in many real-world scenarios, the networks is heterogeneous, dynamical, and in large-scale. This project will propose new approaches, or adapt existing technologies to fit the characteristics of complex network environments. Some key technologies such as dominate set based relationship summary structure generation, non-iterative relationship closeness computation and update strategies, composite relationship definition, general linear model based relationship prediction, mixed probability model based multi-relational collaborative clustering, significantly changed connected sub-graph extraction, and relative index based sub-graph similarity search will be explored. By this way, we can solve the problems of association relationship representation, measuring, prediction, abnormal and loca

英文关键词： Information Network；Association Relationship；Relationship Prediction；Relationship Closeness；Local Aggregation