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小木虫论坛-学术科研互动平台 » 文献求助区 » 检索知识 » 检索方法 » 求助一篇论文是否被检索
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[求助] 求助一篇论文是否被检索

题目: Overlapping community detection in complex networks using symmetric binary matrix factorization
期刊: Physical Review E
卷期号: 87 (6)
页码: 062803
作者: ZhongYuan Zhang, Yong Wang, YongYeol Ahn
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oven1986: 金币+1, 感谢应助。 2013-09-09 18:39:47
oven1986: 检索EPI+1, 感谢应助！ 2013-09-10 17:43:30
SCI可以检索到：
http://apps.webofknowledge.com/f ... age=1&doc=1
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oven1986: 金币+1, 感谢应助。 2013-09-09 18:40:03
WOS:000320280900003
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oven1986: 金币+1, 感谢应助。 2013-09-09 18:40:10
shamolvzhou: 金币+6 2013-09-10 07:38:52
Overlapping community detection in complex networks using symmetric binary matrix factorization



作者: Zhang, ZY (Zhang, Zhong-Yuan)[ 1 ] ; Wang, Y (Wang, Yong)[ 2 ] ; Ahn, YY (Ahn, Yong-Yeol)[ 3 ]



来源出版物: PHYSICAL REVIEW E  卷:87   期:6     文献号:062803   DOI:10.1103/PhysRevE.87.062803   出版年:JUN 12 2013



被引频次: 0 (来自 Web of Science)



引用的参考文献: 33      [ 查看 Related Records ]     引证关系图     



摘要: Discovering overlapping community structures is a crucial step to understanding the structure and dynamics of many networks. In this paper we develop a symmetric binary matrix factorization model to identify overlapping communities. Our model allows us not only to assign community memberships explicitly to nodes, but also to distinguish outliers from overlapping nodes. In addition, we propose a modified partition density to evaluate the quality of community structures. We use this to determine the most appropriate number of communities. We evaluate our methods using both synthetic benchmarks and real-world networks, demonstrating the effectiveness of our approach.



入藏号:WOS:000320280900003



文献类型: Article



语种: English



KeyWords Plus: MODULARITY; PATTERN



通讯作者地址: Zhang, ZY (通讯作者)




Cent Univ Finance & Econ, Sch Stat, Beijing 100081, Peoples R China.






地址:




[ 1 ] Cent Univ Finance & Econ, Sch Stat, Beijing 100081, Peoples R China







[ 2 ] Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China







[ 3 ] Indiana Univ, Sch Informat & Comp, Bloomington, IN 47408 USA






电子邮件地址: zhyuanzh@gmail.com; yyahn@indiana.edu



基金资助致谢:






基金资助机构

授权号



National Natural Science Foundation of China


61203295

11131009

61171007



Program for Innovation Research in Central University of Finance and Economics






[显示基金资助信息]   





出版商:AMER PHYSICAL SOC, ONE PHYSICS ELLIPSE, COLLEGE PK, MD 20740-3844 USA



Web of Science 类别: Physics, Fluids & Plasmas; Physics, Mathematical



研究方向: Physics



IDS 号:162QS



ISSN:1539-3755
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oven1986: 金币+1, 感谢应助。 2013-09-09 18:40:21
shamolvzhou: 金币+4 2013-09-10 07:38:35
EI也可以检索到，两个结果，你自己挑那个是你需要的吧：


Accession number:


13551901





Title:

Overlapping community detection in complex networks using symmetric binary matrix factorization





Authors:

Zhong-Yuan Zhang1 ; Yong Wang2; Yong-Yeol Ahn3





Author affiliation:

1Sch. of Stat., Central Univ. of Finance & Econ., Beijing, China






2Nat. Center for Math. & Interdiscipl. Sci., Acad. of Math. & Syst. Sci., Beijing, China






3Sch. of Inf. & Comput., Indiana Univ., Bloomington, IN, United States





Source title:

Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)





Abbreviated source title:

Phys. Rev. E, Stat. Nonlinear Soft Matter Phys. (USA)





Volume:

87





Issue:

6





Publication date:

June 2013





Pages:

062803 (7 pp.)





Language:

English





ISSN:

1539-3755





CODEN:

PLEEE8





Document type:

Journal article (JA)





Publisher:

American Physical Society





Country of publication:

USA





Material Identity Number:

DQ95-2013-006





Abstract:

Discovering overlapping community structures is a crucial step to understanding the structure and dynamics of many networks. In this paper we develop a symmetric binary matrix factorization model to identify overlapping communities. Our model allows us not only to assign community memberships explicitly to nodes, but also to distinguish outliers from overlapping nodes. In addition, we propose a modified partition density to evaluate the quality of community structures. We use this to determine the most appropriate number of communities. We evaluate our methods using both synthetic benchmarks and real-world networks, demonstrating the effectiveness of our approach.





Number of references:

35





Inspec controlled terms:

complex networks  -  matrix decomposition  -  network theory (graphs)  -  social sciences





Uncontrolled terms:

community detection  -  community structure quality  -  partition density  -  community membership  -  overlapping community identification  -  symmetric binary matrix factorization  -  complex network





Inspec classification codes:

C1290P Systems theory applications in social science and politics -  C1110 Algebra -  C1160 Combinatorial mathematics





Treatment:

Theoretical or Mathematical (THR)





Discipline:

Computers/Control engineering (C)





DOI:

10.1103/PhysRevE.87.062803





Database:

Inspec






Copyright 2013, The Institution of Engineering and Technology



Full-text and Local Holdings Links





另一个：

Accession number:


20132716470678





Title:

Overlapping community detection in complex networks using symmetric binary matrix factorization





Authors:

Zhang, Zhong-Yuan1 ; Wang, Yong2; Ahn, Yong-Yeol3





Author affiliation:

1School of Statistics, Central University of Finance and Economics, Haidian District, Beijing 100081, China






2National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China






3School of Informatics and Computing, Indiana University, Bloomington, IN 47408, United States





Corresponding author:

Zhang, Z.-Y. (zhyuanzh@gmail.com)





Source title:

Physical Review E - Statistical, Nonlinear, and Soft Matter Physics





Abbreviated source title:

Phys. Rev. E Stat. Nonlinear Soft Matter Phys.





Volume:

87





Issue:

6





Issue date:

June 12, 2013





Publication year:

2013





Article number:

062803





Language:

English





ISSN:

15393755





E-ISSN:

15502376





CODEN:

PLEEE8





Document type:

Journal article (JA)





Publisher:

American Physical Society, One Physics Ellipse, College Park, MD 20740-3844, United States





Abstract:

Discovering overlapping community structures is a crucial step to understanding the structure and dynamics of many networks. In this paper we develop a symmetric binary matrix factorization model to identify overlapping communities. Our model allows us not only to assign community memberships explicitly to nodes, but also to distinguish outliers from overlapping nodes. In addition, we propose a modified partition density to evaluate the quality of community structures. We use this to determine the most appropriate number of communities. We evaluate our methods using both synthetic benchmarks and real-world networks, demonstrating the effectiveness of our approach. © 2013 American Physical Society.





Number of references:

35





Main heading:

Quality control





Controlled terms:

Social sciences





Uncontrolled terms:

Binary matrix  -  Community structures  -  Overlapping communities  -  Overlapping community detections  -  Overlapping nodes  -  Real-world networks  -  Structure and dynamics  -  Synthetic benchmark





Classification code:

913.3 Quality Assurance and Control -  971 Social Sciences





DOI:

10.1103/PhysRevE.87.062803





Database:

Compendex






Compilation and indexing terms, © 2013 Elsevier Inc.
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