检索结果-内蒙古大学图书馆

Improving community detection algorithms in directed graphs with fuzzy measures. An application to mobility networks

引用

EXPERT SYSTEMS WITH APPLICATIONS 2025年 269卷

作者： Garcia-Pardo, Inmaculada Gutierrez Perez, Maria Barroso Gonzalez, Daniel Gomez Cantalejo, Javier Castro Univ Complutense Madrid Fac Stat Studies Madrid Spain

This paper proposes a novel methodology to enhance any community detection algorithm for directed networks by introducing a flow-based fuzzy measure, which improves both partition quality and the interpretability of the algorithm. To do so, we focus on a novel aggregation paradigm which combines social networks with fuzzy measures. We explore the potential of incorporating information from fuzzy measures, specifically with a flow capacity measure, to improve and optimize community detection algorithms. We present a detailed evaluation process to demonstrate the effectiveness of this methodology. To achieve this, we analyze a robust repository of databases, using several classical community detection techniques. A comprehensive comparison of classic results with the new methodology demonstrates the effectiveness of the presented aggregation paradigm. We reach amore conclusive understanding of the impact of our methodology through the application of machine learning techniques. Therefore, the proposed methodology enhances community detection performance in directed networks by incorporating flow-based fuzzy measures. We also illustrate its effectiveness through a case study. It showcases improved partition quality compared to traditional algorithms, along with theoretical insights into the fuzzy approach.

关键词： community detection problems Fuzzy measures Aggregation Flow capacity measure Social network analysis Machine learning

来源：评论

学校读者我要写书评

暂无评论

An improved multi-objective evolutionary algorithm for simultaneously detecting separated and overlapping communities

引用

NATURAL COMPUTING 2016年第4期15卷 635-651页

作者： Liu, Chenlong Liu, Jing Jiang, Zhongzhou Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710071 Peoples R China

In our previous work, a multi-objective evolutionary algorithm (MEA_CDPs) was proposed for detecting separated and overlapping communities simultaneously. However, MEA_CDPs has a couple of defects, like individuals cannot be transformed to community structure by the decoder when the quality of community structure is lower certain thresholds, many vertices with weak overlapping nature are identified as overlapping nodes, and the objective functions can not control the ratio of separated nodes to overlapping nodes. Therefore, in this paper, to overcome these defects, we improve MEA_CDPs by designing more efficient objective functions. We also extend MEA_CDPs' capability in detecting hierarchical community structures. The improved algorithm is named as iMEA_CDPs. In the experiments, a set of computer-generated networks are first used to test the effect of parameters in iMEA_CDPs, and then four real-world networks are used to validate the performance of iMEA_CDPs. The experimental results show that iMEA_CDPs outperforms MEA_CDPs. Moreover, compared with MEA_CDPs, iMEA_CDPs can detect various kinds of overlapping and hierarchical community structures.

关键词： Evolutionary algorithms Multi-objective optimization problems community detection problems Overlapping communities Separated communities

来源：评论

学校读者我要写书评

暂无评论

Traveling salesman problems with PageRank Distance on complex networks reveal community structure

引用

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2016年第0期463卷 293-302页

作者： Jiang, Zhongzhou Liu, Jing Wang, Shuai Xidian Univ Minist Educ Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China

In this paper, we propose a new algorithm for community detection problems (CDPs) based on traveling salesman problems (TSPs), labeled as TSP-CDA. Since TSPs need to find a tour with minimum cost, cities close to each other are usually clustered in the tour. This inspired us to model CDPs as TSPs by taking each vertex as a city. Then, in the final tour, the vertices in the same community tend to cluster together, and the community structure can be obtained by cutting the tour into a couple of paths. There are two challenges. The first is to define a suitable distance between each pair of vertices which can reflect the probability that they belong to the same community. The second is to design a suitable strategy to cut the final tour into paths which can form communities. In TSP-CDA, we deal with these two challenges by defining a PageRank Distance and an automatic threshold-based cutting strategy. The PageRank Distance is designed with the intrinsic properties of CDPs in mind, and can be calculated efficiently. In the experiments, benchmark networks with 1000-10,000 nodes and varying structures are used to test the performance of TSP-CDA. A comparison is also made between TSP-CDA and two well established community detection algorithms. The results show that TSP-CDA can find accurate community structure efficiently and outperforms the two existing algorithms. (C) 2016 Elsevier B.V. All rights reserved.

关键词： community detection problems Traveling salesman problems PageRank

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of evolutionary and memetic algorithms for community detection from signed social networks

引用

SOFT COMPUTING 2014年第2期18卷 329-348页

作者： Li, Yadong Liu, Jing Liu, Chenlong Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710071 Peoples R China

To detect communities in signed networks consisting of both positive and negative links, two new evolutionary algorithms (EAs) and two new memetic algorithms (MAs) are proposed and compared. Furthermore, two measures, namely the improved modularity Q and the improved modularity density D-value, are used as the objective functions. The improved measures not only preserve all properties of the original ones, but also have the ability of dealing with negative links. Moreover, D-value can also control the partition to different resolutions. To fully investigate the performance of these four algorithms and the two objective functions, benchmark social networks and various large-scale randomly generated signed networks are used in the experiments. The experimental results not only show the capability and high efficiency of the four algorithms in successfully detecting communities from signed networks, but also indicate that the two MAs outperform the two EAs in terms of the solution quality and the computational cost. Moreover, by tuning the parameter in D-value, the four algorithms have the multi-resolution ability.

关键词： Signed social networks Memetic algorithms Evolutionary algorithms community detection problems

来源：评论

学校读者我要写书评

暂无评论

A Multiobjective Evolutionary Algorithm Based on Similarity for community detection from Signed Social Networks

引用

IEEE TRANSACTIONS ON CYBERNETICS 2014年第12期44卷 2274-2287页

作者： Liu, Chenlong Liu, Jing Jiang, Zhongzhou Xidian Univ Minist Educ Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China

Various types of social relationships, such as friends and foes, can be represented as signed social networks (SNs) that contain both positive and negative links. Although many community detection (CD) algorithms have been proposed, most of them were designed primarily for networks containing only positive links. Thus, it is important to design CD algorithms which can handle large-scale SNs. To this purpose, we first extend the original similarity to the signed similarity based on the social balance theory. Then, based on the signed similarity and the natural contradiction between positive and negative links, two objective functions are designed to model the problem of detecting communities in SNs as a multiobjective problem. Afterward, we propose a multiobjective evolutionary algorithm, called MEA(s) SN. In MEA(s)-SN, to overcome the defects of direct and indirect representations for communities, a direct and indirect combined representation is designed. Attributing to this representation, MEA(s)-SN can switch between different representations during the evolutionary process. As a result, MEA(s)-SN can benefit from both representations. Moreover, owing to this representation, MEA(s)-SN can also detect overlapping communities directly. In the experiments, both benchmark problems and large-scale synthetic networks generated by various parameter settings are used to validate the performance of MEA(s)-SN. The experimental results show the effectiveness and efficacy of MEA(s)-SN on networks with 1000, 5000, and 10 000 nodes and also in various noisy situations. A thorough comparison is also made between MEA(s)-SN and three existing algorithms, and the results show that MEA(s)-SN outperforms other algorithms.

关键词： community detection problems direct representation indirect representation multiobjective evolutionary algorithms signed social networks similarity

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：