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EasyGraph

From EverybodyWiki Bios & Wiki



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EasyGraph
Developer(s)Min Gao, Zhen Li, Ruichen Li, Chenhao Cui, Xinyuan Chen, Bodian Ye, jiawei Li, Haoran Qin, Xinlei He, Yi Sun, Yuting Shao, Zihang Lin, Yang Chen, Qingyuan Gong
Initial release7 August 2023; 10 months ago (2023-08-07)[1]
Written inPython, C++
Engine
    Operating systemLinux, Windows, macOS
    Size3.2 MB
    Available inEnglish
    TypeProgramming
    LicenseBSD-3-Clause
    Websiteeasy-graph.github.io/index.html

    Search EasyGraph on Amazon.

    EasyGraph[2][3] is an open-source network analysis and network embedding[4] software package. It is mainly written in Python and supports analysis for undirected networks and directed networks. EasyGraph supports various formats of network data and covers a series of important network analysis algorithms for node centrality analysis[5] , detecting community structure[6][7] [8], structural hole spanner detection[9][10][11][12], and graph representation[13] [14][15] [16] [17]. Moreover, EasyGraph implements some key elements using C++ and introduces multiprocessing optimization[18] 

    to achieve better efficiency.

    History[edit]

    EasyGraph was developed by the DataNET group at Fudan University. Our goal is to build a cross-platform library which could be useful for interdisciplinary network analytics.

    It's first version 1.0 has been launched in 2023.

    Applications[edit]

    EasyGraph has multiple notable applications including basic properties and operation of networks[19][20]

    , detection of structural hole spanners, network embedding[21] [22][23] [24] [25], network construction[26] , and community detection[27] .

    See also[edit]

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    File formats
    Related software

    References[edit]

    1. ↑ https://github.com/easy-graph/Easy-Graph EasyGraph version 1.0 release date
    2. ↑ Min Gao and Zheng Li and Ruichen Li and Chenhao Cui and Xinyuan Chen and Bodian Ye and Yupeng Li and Weiwei Gu and Qingyuan Gong and Xin Wang and Yang Chen (2023). "EasyGraph: A Multifunctional, Cross-Platform, and Effective Library for Interdisciplinary Network Analysis". Patterns. 4 (10): 100839. doi:10.1016/j.patter.2023.100839. PMC 10591136 Check |pmc= value (help). PMID 37876903 Check |pmid= value (help).
    3. ↑ EasyGraph (2023-10-13). EasyGraph Tutorials. YouTube.
    4. ↑ Grover, Aditya; Leskovec, Jure (2016). "Node2vec". Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016. pp. 855–864. arXiv:1607.00653. Bibcode:2016arXiv160700653G. doi:10.1145/2939672.2939754. ISBN 9781450342322. PMC 5108654. PMID 27853626. Search this book on
    5. ↑ Freeman, L.C. (1978). "Centrality in social networks conceptual clarification". Soc. Network. 1 (3): 215–239. doi:10.1016/0378-8733(78)90021-7.
    6. ↑ Newman, M.E.J. (2012). "Communities, modules and large-scale structure in networks". Nat. Phys. 8 (1): 25–31. Bibcode:2012NatPh...8...25N. doi:10.1038/nphys2162. Unknown parameter |s2cid= ignored (help)
    7. ↑ Kong, Y.-X., Shi, G.-Y., Wu, R.-J., and Zhang, Y.-C. (2019). "k-core: Theories and applications". Phys. Rep. 832: 1–32. Bibcode:2019PhR...832....1K. doi:10.1016/j.physrep.2019.10.004. Unknown parameter |s2cid= ignored (help)CS1 maint: Multiple names: authors list (link)
    8. ↑ Su, X., Xue, S., Liu, F., Wu, J., Yang, J., Zhou, C., Hu, W., Paris, C., Nepal, S., Jin, D., Sheng, Q., Yu, Philip S. (2022). "A comprehensive survey on community detection with deep learning". IEEE Trans. Neural Netw. Learn. Syst. PP (4): 1–21. arXiv:2105.12584. doi:10.1109/TNNLS.2021.3137396. PMID 35263257 Check |pmid= value (help).CS1 maint: Multiple names: authors list (link)
    9. ↑ Burt, R. (2004). "Structural holes and good ideas". American Journal of Sociology. 110 (2): 349–399. CiteSeerX 10.1.1.388.2251. doi:10.1086/421787. Unknown parameter |s2cid= ignored (help)
    10. ↑ Li, W., Xu, Z., Sun, Y., Gong, Q., Chen, Y., Ding, A.Y., Wang, X., and Hui, P. (2023). "DeepPick: A Deep Learning Approach to Unveil Outstanding Users with Public Attainable Features". IEEE Trans. Knowl. Data Eng. 35: 291–306. doi:10.1109/TKDE.2021.3091503. Unknown parameter |s2cid= ignored (help)CS1 maint: Multiple names: authors list (link)
    11. ↑ Yang, L., Holtz, D., Jaffe, S., Suri, S., Sinha, S., Weston, J., Joyce, C., Shah, N., Sherman, K., Hecht, B., and Teevan, J. (2022). "The effects of remote work on collaboration among information workers". Nat. Hum. Behav. 6 (1): 43–54. doi:10.1038/s41562-021-01196-4. PMID 34504299 Check |pmid= value (help).CS1 maint: Multiple names: authors list (link)
    12. ↑ Li, P., Sun, X., Zhang, K., Zhang, J., and Kurths, J. (2016). "Role of structural holes in containing spreading processes". Phys. Rev. E. 93 (3): 032312. Bibcode:2016PhRvE..93c2312L. doi:10.1103/PhysRevE.93.032312. PMC 7217494 Check |pmc= value (help). PMID 27078371.CS1 maint: Multiple names: authors list (link)
    13. ↑ Liu, Y., Ao, X., Qin, Z., Chi, J., Feng, J., Yang, H., and He, Q. (2021). "Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection". Proceedings of the Web Conference 2021. pp. 3168–3177. doi:10.1145/3442381.3449989. ISBN 978-1-4503-8312-7.CS1 maint: Multiple names: authors list (link) Search this book on
    14. ↑ Perozzi, B., Al-Rfou, R., and Skiena, S. (2014). "DeepWalk: Online learning of social representations". Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. pp. 701–710. arXiv:1403.6652. doi:10.1145/2623330.2623732. ISBN 978-1-4503-2956-9.CS1 maint: Multiple names: authors list (link) Search this book on
    15. ↑ Grover, A., and Leskovec, J. (2016). "Node2vec: Scalable Feature Learning for Networks". Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016. pp. 855–864. doi:10.1145/2939672.2939754. ISBN 978-1-4503-4232-2. PMC 5108654. PMID 27853626.CS1 maint: Multiple names: authors list (link) Search this book on
    16. ↑ Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., and Mei, Q. (2015). "LINE: Large-scale Information Network Embedding". Proceedings of the 24th International Conference on World Wide Web. pp. 1067–1077. arXiv:1503.03578. doi:10.1145/2736277.2741093. ISBN 978-1-4503-3469-3. Unknown parameter |s2cid= ignored (help)CS1 maint: Multiple names: authors list (link) Search this book on
    17. ↑ Wang, D., Cui, P., and Zhu, W. (2016). "Structural Deep Network Embedding". Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 1225–1234. doi:10.1145/2939672.2939753. ISBN 978-1-4503-4232-2. Unknown parameter |s2cid= ignored (help)CS1 maint: Multiple names: authors list (link) Search this book on
    18. ↑ Aziz, Z. A., Abdulqader, D. N., Sallow, A. B., & Omer, H. K. (2021). "Python parallel processing and multiprocessing: A review". Academic Journal of Nawroz University. 10 (3): 345–354. doi:10.25007/ajnu.v10n3a1145.CS1 maint: Multiple names: authors list (link)
    19. ↑ Newman, M.E. (2018). Networks. Oxford University Press. doi:10.1093/oso/9780198805090.001.0001. ISBN 978-0-19-880509-0. Search this book on
    20. ↑ Broido, A.D., and Clauset, A. (2019). "Scale-free networks are rare". Nat. Commun. 10 (1): 1017–1010. arXiv:1801.03400. Bibcode:2019NatCo..10.1017B. doi:10.1038/s41467-019-08746-5. PMC 6399239. PMID 30833554.CS1 maint: Multiple names: authors list (link)
    21. ↑ Liu, Y., Ao, X., Qin, Z., Chi, J., Feng, J., Yang, H., and He, Q. (2021). "Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection". Proceedings of the Web Conference 2021. pp. 3168–3177. doi:10.1145/3442381.3449989. ISBN 978-1-4503-8312-7.CS1 maint: Multiple names: authors list (link) Search this book on
    22. ↑ Perozzi, B., Al-Rfou, R., and Skiena, S. (2014). "DeepWalk: Online learning of social representations". Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. pp. 701–710. arXiv:1403.6652. doi:10.1145/2623330.2623732. ISBN 978-1-4503-2956-9.CS1 maint: Multiple names: authors list (link) Search this book on
    23. ↑ Grover, A., and Leskovec, J. (2016). "Node2vec: Scalable Feature Learning for Networks". Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016. pp. 855–864. doi:10.1145/2939672.2939754. ISBN 978-1-4503-4232-2. PMC 5108654. PMID 27853626.CS1 maint: Multiple names: authors list (link) Search this book on
    24. ↑ Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., and Mei, Q. (2015). "LINE: Large-scale Information Network Embedding". Proceedings of the 24th International Conference on World Wide Web. pp. 1067–1077. arXiv:1503.03578. doi:10.1145/2736277.2741093. ISBN 978-1-4503-3469-3. Unknown parameter |s2cid= ignored (help)CS1 maint: Multiple names: authors list (link) Search this book on
    25. ↑ Wang, D., Cui, P., and Zhu, W. (2016). "Structural Deep Network Embedding". Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 1225–1234. doi:10.1145/2939672.2939753. ISBN 978-1-4503-4232-2. Unknown parameter |s2cid= ignored (help)CS1 maint: Multiple names: authors list (link) Search this book on
    26. ↑ Faust, K. (2021). "Open challenges for microbial network construction and analysis". The ISME Journal. 15 (11): 3111–3118. Bibcode:2021ISMEJ..15.3111F. doi:10.1038/s41396-021-01027-4. PMC 8528840 Check |pmc= value (help). PMID 34108668 Check |pmid= value (help).
    27. ↑ Fortunato, S. (2010). "Community detection in graphs". Physics Reports. 486 (3–5): 75–174. arXiv:0906.0612. Bibcode:2010PhR...486...75F. doi:10.1016/j.physrep.2009.11.002.
    28. ↑ "Pajek / PajekXXL / Pajek3XL". mrvar.fdv.uni-lj.si. Retrieved 2019-12-09.

    External links[edit]


    This article "EasyGraph" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:EasyGraph. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.


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