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| 基于典型相关分析的复杂网络模块挖掘算法 | |
| 引用本文： | 叶育鑫,赵建民,莫毓昌,欧阳丹彤,刘华文.基于典型相关分析的复杂网络模块挖掘算法[J].吉林大学学报(工学版),2013,43(2):424-428. |
| 作者姓名： | 叶育鑫 赵建民 莫毓昌 欧阳丹彤 刘华文 |
| 作者单位： | 1. 吉林大学计算机科学与技术学院,长春130012;吉林大学符号计算与知识工程教育部重点实验室,长春130012 2. 浙江师范大学数理与信息工程学院,浙江金华,321004 3. 吉林大学符号计算与知识工程教育部重点实验室,长春130012;浙江师范大学数理与信息工程学院,浙江金华321004 |
| 基金项目： | 国家自然科学基金项目(60973089,61170314,41172294,61100119,60903011);浙江省自然科学基金项目(Y1100689);浙江师范大学计算机软件与理论省级重中之重学科开放基金项目(ZSDZZZZXK10,ZSDZZZZXK05);吉林大学符号计算与知识工程教育部重点实验室开放项目(93K-17-2009-K05,93K-17-2010-K02) |
| 摘 要： | 利用典型相关分析(CCA)分析了复杂网络中的功能模块及其相互关系,并将其转化为LASSO回归优化问题,提高了结果的可解释性。在此基础上,提出了一种模块及其相互关系的挖掘算法。该算法不仅能准确挖掘网络中的功能模块,而且还能同时度量模块之间的相关程度。人工生成数据集和DBLP数据集上的模拟实验表明,提出的算法能准确地挖掘网络中的功能模块及其相关性。 |
| 关 键 词： | 计算机软件 复杂网络 功能模块 社交网络分析 典型相关分析 |
CCA-based mining algorithm of modules in in complex networks |
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| YE Yu-xin,ZHAO Jian-min,MO Yu-chang,OUYANG Dan-tong,LIU Hua-wen.CCA-based mining algorithm of modules in in complex networks[J].Journal of Jilin University:Eng and Technol Ed,2013,43(2):424-428. | |
| Authors: | YE Yu-xin ZHAO Jian-min MO Yu-chang OUYANG Dan-tong LIU Hua-wen |
| Affiliation: | 2,3(1.College of Computer Science and Technology,Jilin University,Changchun 130012,China;2.Key Lab of Symbol Computation and Knowledge Engineer of Ministry of Education,Jilin University,Changchun 130012,China;3.College of Mathematics,Physics and Information Engineering,Zhejiang Normal University,Jinhua 321004,China) |
| Abstract: | Complex networks,such as social networks and biological networks,are ubiquitous in real world.Identifying modules and their relationships in complex networks is very important to discover entities and modules behind the networks,and to understand the mechanisms of the networks.In this paper,we analyze modules and their interplays in complex network using Canonical Correlation Analysis(CCA).To improve the interpretability of the results,we further extend the solution of CCA as a LASSO optimization problem,and then propose a new mining algorithm of modules and their relationships.This algorithm enables us to disclose modules and explicitly modeling their relationships simultaneously.Extensive experiments on both synthetic and DBLP datasets demonstrate the effectiveness of the proposed method. |
| Keywords: | computer software complex network functional module social network canonical correlation analysis(CCA) |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
