一种面向语义重叠社区发现的 Block 场取样算法

辛宇; 杨静; 谢志强

doi:10.16383/j.aas.2015.c140136

一种面向语义重叠社区发现的 Block 场取样算法

doi: 10.16383/j.aas.2015.c140136

辛宇¹,
杨静^1, ,,
谢志强²

1.
哈尔滨工程大学计算机科学与技术学院哈尔滨 150001;
2.
哈尔滨理工大学计算机科学与技术学院哈尔滨 150080

基金项目:

国家自然科学基金(61370083,61073043,61073041,61370086),国家教育部博士点基金(20112304110011,20122304110012)资助

详细信息

作者简介:
辛宇哈尔滨工程大学计算机科学与技术学院博士研究生. 2011 年获哈尔滨理工大学计算机科学与技术学院硕士学位. 主要研究方向为数据库与知识工程.E-mail: xinyu@hrbeu.edu.cn

通讯作者:
杨静哈尔滨工程大学计算机科学与技术学院教授. 主要研究方向为数据库与知识工程. 本文通信作者.E-mail: yangjing@hrbeu.edu.cn

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- 文章访问数: 1717
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出版历程
- 收稿日期: 2014-03-14
- 修回日期: 2014-08-12
- 刊出日期: 2015-02-20

An Overlapping Community Structure Detecting Algorithm in Semantic Social Network Based on Block Field

1.
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001;
2.
College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080

Funds:

Supported by National Natural Science Foundation of China (61370083, 61073043, 61073041, 61370086) and National Research Foundation for the Doctoral Program of Higher Education of China (20112304110011, 20122304110012)

摘要

摘要: 语义社会网络(Semantic social network, SSN)是一种包含信息节点及社会关系构成的新型复杂网络. 传统语义社会网络分析算法在进行社区挖掘时, 需要预先设定社区个数且无法发现重叠社区. 针对这一问题, 提出一种面向语义重叠社区发现的block场采样算法, 该算法首先以LDA (Latent dirichlet allocation)模型为语义分析模型, 建立了以取样节点为核心节点的block 场BAT (Block-author-topic)模型; 其次, 根据节点的语义分析结果, 建立可度量block区域的语义凝聚力方法, 实现了语义信息的可度量化; 最后, 以节点的语义凝聚力为输入, 改进了重叠社区发现的标签传播算法(Label propagation algorithm, LPA)及可评价语义社区的SQ度量模型, 并通过实验分析, 验证了本文算法及SQ 度量模型的有效性及可行性.
- 语义社会网络 /
- 重叠社区 /
- LDA模型 /
- 社区发现
Abstract: The semantic social network (SSN) is a new kind of complex networks consisting of the node content and topological relationship. The traditional community detection algorithms need to preset the number of the communities and could not detect the overlapping communities. To solve this problem, an overlapping community structure detecting algorithm in semantic social network based on the block field is proposed. Firstly, it takes the latent dirichlet allocation (LDA) model as the semantic analyzing model, establishing the block-author-topic (BAT) model with the sampling node as the core node. Secondly, it suggests the measurement of the semantic cohesion of the block field, depending on the analysis of SSN, to achieve the evaluation of semantic information. Finally, it improves the label propagation algorithm (LPA) which could detect the overlapping communities, with the semantic cohesion as input, and designs the SQ measurement modularity for semantic measuring. The efficiency and feasibility of the algorithm and the semantic modularity are verified via experimental analysis.
- Semantic social network /
- overlapping community /
- latent dirichlet allocation (LDA) /
- community detection

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参考文献(32)

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一种面向语义重叠社区发现的 Block 场取样算法

doi: 10.16383/j.aas.2015.c140136

作者简介:
辛宇哈尔滨工程大学计算机科学与技术学院博士研究生. 2011 年获哈尔滨理工大学计算机科学与技术学院硕士学位. 主要研究方向为数据库与知识工程.E-mail: xinyu@hrbeu.edu.cn

通讯作者:
杨静哈尔滨工程大学计算机科学与技术学院教授. 主要研究方向为数据库与知识工程. 本文通信作者.E-mail: yangjing@hrbeu.edu.cn

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An Overlapping Community Structure Detecting Algorithm in Semantic Social Network Based on Block Field

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留言板

一种面向语义重叠社区发现的 Block 场取样算法

doi: 10.16383/j.aas.2015.c140136

作者简介: 辛宇 哈尔滨工程大学计算机科学与技术学院博士研究生. 2011 年获哈尔滨理工大学计算机科学与技术学院硕士学位. 主要研究方向为数据库与知识工程.E-mail: xinyu@hrbeu.edu.cn

通讯作者: 杨静 哈尔滨工程大学计算机科学与技术学院教授. 主要研究方向为数据库与知识工程. 本文通信作者.E-mail: yangjing@hrbeu.edu.cn

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出版历程

An Overlapping Community Structure Detecting Algorithm in Semantic Social Network Based on Block Field

计量

出版历程

目录

作者简介:
辛宇哈尔滨工程大学计算机科学与技术学院博士研究生. 2011 年获哈尔滨理工大学计算机科学与技术学院硕士学位. 主要研究方向为数据库与知识工程.E-mail: xinyu@hrbeu.edu.cn

通讯作者:
杨静哈尔滨工程大学计算机科学与技术学院教授. 主要研究方向为数据库与知识工程. 本文通信作者.E-mail: yangjing@hrbeu.edu.cn