var bibbase_data = {"data":"\"Loading..\"\n\n
\n\n \n\n \n\n \n \n\n \n\n \n \n\n \n\n \n
\n generated by\n \n \"bibbase.org\"\n\n \n
\n \n\n
\n\n \n\n\n
\n\n Excellent! Next you can\n create a new website with this list, or\n embed it in an existing web page by copying & pasting\n any of the following snippets.\n\n
\n JavaScript\n (easiest)\n
\n \n <script src=\"https://bibbase.org/show?bib=http%3A%2F%2Fweb.eecs.umich.edu%2F%7Edkoutra%2Ftut%2Ficdm18_summarization.bib&jsonp=1&group0=part&folding=1&jsonp=1\"></script>\n \n
\n\n PHP\n
\n \n <?php\n $contents = file_get_contents(\"https://bibbase.org/show?bib=http%3A%2F%2Fweb.eecs.umich.edu%2F%7Edkoutra%2Ftut%2Ficdm18_summarization.bib&jsonp=1&group0=part&folding=1\");\n print_r($contents);\n ?>\n \n
\n\n iFrame\n (not recommended)\n
\n \n <iframe src=\"https://bibbase.org/show?bib=http%3A%2F%2Fweb.eecs.umich.edu%2F%7Edkoutra%2Ftut%2Ficdm18_summarization.bib&jsonp=1&group0=part&folding=1\"></iframe>\n \n
\n\n

\n For more details see the documention.\n

\n
\n
\n\n
\n\n This is a preview! To use this list on your own web site\n or create a new web site from it,\n create a free account. The file will be added\n and you will be able to edit it in the File Manager.\n We will show you instructions once you've created your account.\n
\n\n
\n\n

To the site owner:

\n\n

Action required! Mendeley is changing its\n API. In order to keep using Mendeley with BibBase past April\n 14th, you need to:\n

    \n
  1. renew the authorization for BibBase on Mendeley, and
  2. \n
  3. update the BibBase URL\n in your page the same way you did when you initially set up\n this page.\n
  4. \n
\n

\n\n

\n \n \n Fix it now\n

\n
\n\n
\n\n\n
\n \n \n
\n
\n  \n 0 Survey\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Graph Summarization Methods and Applications: A Survey.\n \n \n \n \n\n\n \n Liu, Y.; Safavi, T.; Dighe, A.; and Koutra, D.\n\n\n \n\n\n\n ACM Computing Surveys, 51(3): 62:1–62:34. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"Graph paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{LiuSDK18,\n  author    = {Yike Liu and\n               Tara Safavi and\n               Abhilash Dighe and\n               Danai Koutra},\n  title     = {Graph Summarization Methods and Applications: {A} Survey},\n  journal   = {{ACM} Computing Surveys},\n  volume    = {51},\n  number    = {3},\n  pages     = {62:1--62:34},\n  year      = {2018},\n  url_Paper = {https://arxiv.org/abs/1612.04883},\n  part = {0 Survey}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n Part I: Network-level Summaries\n \n \n (11)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n PERSEUS-HUB: Interactive and Collective Exploration of Large-scale Graphs.\n \n \n \n \n\n\n \n Jin, D.; Leventidis, A.; Shen, H.; Zhang, R.; Wu, J.; and Koutra, D.\n\n\n \n\n\n\n Informatics (Special Issue ``Scalable Interactive Visualization''), 4(3). 2017.\n \n\n\n\n
\n\n\n\n \n \n \"PERSEUS-HUB: paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{JinLSZWK17,\n                title = {{PERSEUS-HUB: Interactive and Collective Exploration of Large-scale\n                        Graphs}},\n                author = {Di Jin and Aristotelis Leventidis and Haoming Shen and Ruowang Zhang and\n                        Junyue Wu and Danai Koutra},\n                year = {2017},\n                volume = {4}, \n                number = {3}, \n                issue = {2227-9709},\n                journal = {Informatics (Special Issue ``Scalable Interactive Visualization'')},\n                url_Paper = {http://www.mdpi.com/2227-9709/4/3/22},\n                part = {Part I: Network-level Summaries},\n}    \n\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Graph stream summarization: From big bang to big crunch.\n \n \n \n \n\n\n \n Tang, N.; Chen, Q.; and Mitra, P.\n\n\n \n\n\n\n In Proceedings of the 2016 ACM International Conference on Management of Data (SIGMOD), pages 1481–1496, 2016. ACM\n \n\n\n\n
\n\n\n\n \n \n \"Graph paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InProceedings{tang2016graph,\n        author       = {Tang, Nan and Chen, Qing and Mitra, Prasenjit},\n        title        = {Graph stream summarization: From big bang to big crunch},\n        booktitle    = {Proceedings of the 2016 ACM International Conference on Management of Data (SIGMOD)},\n        year         = {2016},\n        pages        = {1481--1496},\n        organization = {ACM},\n        url_Paper =  {http://da.qcri.org/ntang/pubs/[sigmod2016]graph.stream.summarization.pdf},\n        part = {Part I: Network-level Summaries}\n}\n\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Reducing large graphs to small supergraphs: a unified approach.\n \n \n \n \n\n\n \n Liu, Y.; Safavi, T.; Shah, N.; and Koutra, D.\n\n\n \n\n\n\n Social Netw. Analys. Mining, 8(1): 17. 2018.\n \n\n\n\n
\n\n\n\n \n \n \"Reducing paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{DBLP:journals/snam/LiuSSK18,\n  author    = {Yike Liu and\n               Tara Safavi and\n               Neil Shah and\n               Danai Koutra},\n  title     = {Reducing large graphs to small supergraphs: a unified approach},\n  journal   = {Social Netw. Analys. Mining},\n  volume    = {8},\n  number    = {1},\n  pages     = {17},\n  year      = {2018},\n url_Paper = {http://web.eecs.umich.edu/~dkoutra/papers/18_Condense-SNAM.pdf},\n part = {Part I: Network-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n CSI: Community-level Social Influence Analysis.\n \n \n \n\n\n \n Mehmood, Y.; Barbieri, N.; Bonchi, F.; and Ukkonen, A.\n\n\n \n\n\n\n In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pages 48–63. Springer, 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@incollection{Mehmood2013,\n  title={{CSI: Community-level Social Influence Analysis}},\n  author={Mehmood, Yasir and Barbieri, Nicola and Bonchi, Francesco and Ukkonen, Antti},\n  booktitle={Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)},\n  pages={48--63},\n  year={2013},\n  publisher={Springer},\n  part = {Part I: Network-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Graph Summarization with Quality Guarantees.\n \n \n \n\n\n \n Riondato, M.; García-Soriano, D.; and Bonchi, F.\n\n\n \n\n\n\n In Proceedings of the 14th IEEE International Conference on Data Mining (ICDM), 2014. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{RiondatoGB14,\n author = {Riondato, Matteo and Garc\\'{\\i}a-Soriano, David and Bonchi, Francesco},\n title = {Graph Summarization with Quality Guarantees},\n booktitle = {Proceedings of the 14th IEEE International Conference on Data Mining (ICDM)},\n year = {2014},\n part = {Part I: Network-level Summaries}\n}\n\n\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Summarizing and Understanding Large Graphs.\n \n \n \n \n\n\n \n Koutra, D.; Kang, U; Vreeken, J.; and Faloutsos, C.\n\n\n \n\n\n\n In Statistical Analysis and Data Mining, 2015. John Wiley & Sons, Inc.\n \n\n\n\n
\n\n\n\n \n \n \"Summarizing paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InProceedings{   koutra:15:vogJournal,\n  author        = {Danai Koutra and {U} Kang and Jilles Vreeken and Christos Faloutsos},\n  title         = {{Summarizing and Understanding Large Graphs}},\n  booktitle     = {Statistical Analysis and Data Mining},\n  publisher     = {John Wiley \\& Sons, Inc.}, \n  year          = {2015},\n  url_Paper = {http://web.eecs.umich.edu/~dkoutra/papers/VoG_journal.pdf},\n   part = {Part I: Network-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Set-based approximate approach for lossless graph summarization.\n \n \n \n\n\n \n Khan, K.; Nawaz, W.; and Lee, Y.\n\n\n \n\n\n\n Computing, 97(12): 1185–1207. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{KhanNL15,\n  author    = {Kifayat{-}Ullah Khan and\n               Waqas Nawaz and\n               Young{-}Koo Lee},\n  title     = {Set-based approximate approach for lossless graph summarization},\n  journal   = {Computing},\n  volume    = {97},\n  number    = {12},\n  pages     = {1185--1207},\n  year      = {2015},\n   part = {Part I: Network-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Graph Summarization for Attributed Graphs.\n \n \n \n\n\n \n Wu, Y.; Zhong, Z.; Xiong, W.; and Jing, N.\n\n\n \n\n\n\n In 2014 International Conference on Information Science, Electronics and Electrical Engineering (ISEEE), pages 503–507, 2014. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{WuZXJ14,\n  author    = {Ye Wu and\n               Zhinong Zhong and\n               Wei Xiong and\n               Ning Jing},\n  title     = {Graph Summarization for Attributed Graphs},\n  booktitle = {2014 International Conference on Information Science, Electronics and Electrical Engineering (ISEEE)},\n  publisher = {IEEE},\n  pages     = {503--507},\n  year      = {2014},\n   part = {Part I: Network-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n VEGAS: Visual influEnce GrAph Summarization on Citation Networks.\n \n \n \n\n\n \n Shi, L.; Tong, H.; Tang, J.; and Lin, C.\n\n\n \n\n\n\n IEEE Transactions on Knowledge and Data Engineering, 27(12): 3417–3431. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{ShiTTL15,\n  author    = {Lei Shi and\n               Hanghang Tong and\n               Jie Tang and\n               Chuang Lin},\n  title     = {{VEGAS: Visual influEnce GrAph Summarization on Citation Networks}},\n  journal   = {{IEEE Transactions on Knowledge and Data Engineering}},\n  volume    = {27},\n  number    = {12},\n  pages     = {3417--3431},\n  year      = {2015},\n   part = {Part I: Network-level Summaries}\n}\n\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n GraSS: Graph Structure Summarization.\n \n \n \n\n\n \n LeFevre, K.; and Terzi, E.\n\n\n \n\n\n\n In Tenth SIAM International Conference on Data Mining (SDM), pages 454-465, 2010. SIAM\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@InProceedings{   LeFevre2010,\n  author        = {LeFevre, Kristen and Terzi, Evimaria},\n  title         = {{GraSS: Graph Structure Summarization}},\n  booktitle     = {Tenth SIAM International Conference on Data Mining (SDM)},\n  publisher     = {{SIAM}},\n  pages         = {454-465},\n  year          = {2010},\n   part = {Part I: Network-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Substructure Discovery Using Minimum Description Length and Background Knowledge.\n \n \n \n\n\n \n Cook, D. J.; and Holder, L. B.\n\n\n \n\n\n\n Journal of Artificial Intelligence Research, 1: 231-255. 1994.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@Article{         cook:94:subdue,\n  author        = {Diane J. Cook and Lawrence B. Holder},\n  title         = {{Substructure Discovery Using Minimum Description Length and Background Knowledge}},\n  journal       = {Journal of Artificial Intelligence Research}, \n  volume        = {1},\n  year          = {1994},\n  pages         = {231-255},\n   part = {Part I: Network-level Summaries}\n}\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n Part II: Multinetwork-level Summaries\n \n \n (5)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Exploratory Analysis of Graph Data by Leveraging Domain Knowledge.\n \n \n \n \n\n\n \n Jin, D.; and Koutra, D.\n\n\n \n\n\n\n In Proceedings of the 17th IEEE International Conference on Data Mining (ICDM), 2017. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"Exploratory paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{JinK17eagle,\n        title={Exploratory Analysis of Graph Data by Leveraging Domain Knowledge},\n        author={Di Jin and Danai Koutra},\n        booktitle={Proceedings of the 17th IEEE International Conference on Data Mining (ICDM)},\n        year={2017},\n        organization={IEEE},\n        url_Paper = {http://web.eecs.umich.edu/~dkoutra/papers/17_EAGLE_ICDM.pdf},\n        part = {Part II: Multinetwork-level Summaries},\n} \n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n On Summarizing Large-Scale Dynamic Graphs.\n \n \n \n \n\n\n \n Shah, N.; Koutra, D.; Jin, L.; Zou, T.; Gallagher, B.; and Faloutsos, C.\n\n\n \n\n\n\n IEEE Data Engineering Bulletin, 40(3): 75–88. 2017.\n \n\n\n\n
\n\n\n\n \n \n \"On paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{ShahKJZGF17,\n  author    = {Neil Shah and\n               Danai Koutra and\n               Lisa Jin and\n               Tianmin Zou and\n               Brian Gallagher and\n               Christos Faloutsos},\n  title     = {On Summarizing Large-Scale Dynamic Graphs},\n  journal   = {{IEEE} Data Engineering Bulletin},\n  volume    = {40},\n  number    = {3},\n  pages     = {75--88},\n  year      = {2017},\n  url_Paper = {http://sites.computer.org/debull/A17sept/issue1.htm},\n  part = {Part II: Multinetwork-level Summaries},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Condensing Temporal Networks using Propagation.\n \n \n \n\n\n \n Adhikari, B.; Zhang, Y.; Bharadwaj, A.; and Prakash, B A.\n\n\n \n\n\n\n In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), pages 417–425, 2017. SIAM\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{adhikari2017condensing,\n  title={Condensing Temporal Networks using Propagation},\n  author={Adhikari, Bijaya and Zhang, Yao and Bharadwaj, Aditya and Prakash, B Aditya},\n  booktitle={Proceedings of the 17th SIAM International Conference on Data Mining (SDM)},\n  pages={417--425},\n  year={2017},\n  organization={SIAM},\n  part = {Part II: Multinetwork-level Summaries},\n  \n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Modeling Co-Evolution Across Multiple Networks.\n \n \n \n\n\n \n Yu, W.; Aggarwal, C. C.; and Wang, W.\n\n\n \n\n\n\n In Proceedings of the 18th SIAM International Conference on Data Mining (SDM), pages 675–683, 2018. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{YuAW18,\n  author    = {Wenchao Yu and\n               Charu C. Aggarwal and\n               Wei Wang},\n  title     = {Modeling Co-Evolution Across Multiple Networks},\n  booktitle = {Proceedings of the 18th SIAM International Conference on Data Mining (SDM)},\n  pages     = {675--683},\n  year      = {2018},\n  part = {Part II: Multinetwork-level Summaries},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n TimeCrunch: Interpretable Dynamic Graph Summarization.\n \n \n \n \n\n\n \n Shah, N.; Koutra, D.; Zou, T.; Gallagher, B.; and Faloutsos, C.\n\n\n \n\n\n\n In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1055–1064, 2015. \n \n\n\n\n
\n\n\n\n \n \n \"TimeCrunch: paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{DBLP:conf/kdd/ShahKZGF15,\n  author    = {Neil Shah and\n               Danai Koutra and\n               Tianmin Zou and\n               Brian Gallagher and\n               Christos Faloutsos},\n  title     = {TimeCrunch: Interpretable Dynamic Graph Summarization},\n  booktitle = {Proceedings of the 21th {ACM} {SIGKDD} International Conference on\n               Knowledge Discovery and Data Mining},\n  pages     = {1055--1064},\n  year      = {2015},\n  url_Paper = {http://web.eecs.umich.edu/~dkoutra/papers/Timecrunch_KDD15.pdf},\n    part = {Part II: Multinetwork-level Summaries},\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n Part III: Node-level Summaries\n \n \n (8)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization.\n \n \n \n\n\n \n Perozzi, B.; and Akoglu, L.\n\n\n \n\n\n\n ACM Transactions on Knowledge Discovery from Data, 12(2): 24:1–24:40. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{PerozziA18,\n  author    = {Bryan Perozzi and\n               Leman Akoglu},\n  title     = {Discovering Communities and Anomalies in Attributed Graphs: Interactive\n               Visual Exploration and Summarization},\n  journal   = {{ACM Transactions on Knowledge Discovery from Data}},\n  volume    = {12}, \n  number    = {2},\n  pages     = {24:1--24:40},\n  year      = {2018},\n  part  = {Part III: Node-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Efficiently summarizing attributed diffusion networks.\n \n \n \n\n\n \n E. Amiri, S.; Chen, L.; and Aditya Prakash, B.\n\n\n \n\n\n\n Data Mining and Knowledge Discovery. 05 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{AmiriLP18_diffusion,\nauthor = {E. Amiri, Sorour and Chen, Liangzhe and Aditya Prakash, B.},\nyear = {2018},\nmonth = {05},\npages = {},\ntitle = {Efficiently summarizing attributed diffusion networks},\njournal = {Data Mining and Knowledge Discovery},\npart = {Part III: Node-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Subjectively Interesting Connecting Trees.\n \n \n \n\n\n \n Adriaens, F.; Lijffijt, J.; and Bie, T. D.\n\n\n \n\n\n\n In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pages 53–69, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{adriaens:17:trees,\n  author    = {Florian Adriaens and\n               Jefrey Lijffijt and\n               Tijl De Bie},\n  title     = {Subjectively Interesting Connecting Trees},\n  booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)},\n  pages     = {53--69},\n  year      = {2017},\n  part = {Part III: Node-level Summaries}\n}\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Bump Hunting in the Dark: Local Discrepancy Maximization on Graphs.\n \n \n \n\n\n \n Gionis, A.; Mathioudakis, M.; and Ukkonen, A.\n\n\n \n\n\n\n IEEE Transactions on Knowledge and Data Engineering, 29(3): 529–542. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{gionis:17:bump,\n  author    = {Aristides Gionis and\n               Michael Mathioudakis and\n               Antti Ukkonen},\n  title     = {Bump Hunting in the Dark: Local Discrepancy Maximization on Graphs},\n  journal   = {{IEEE Transactions on Knowledge and Data Engineering}},\n  volume    = {29},\n  number    = {3},\n  pages     = {529--542},\n  year      = {2017},\n  part = {Part III: Node-level Summaries}\n}\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Local Exceptionality Detection on Social Interaction Networks.\n \n \n \n\n\n \n Atzmueller, M.\n\n\n \n\n\n\n In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pages 298–302, 2016. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{atzmueller:16:social,\n  author    = {Martin Atzmueller},\n  title     = {Local Exceptionality Detection on Social Interaction Networks},\n  booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)},\n  pages     = {298--302},\n  year      = {2016},\n  part = {Part III: Node-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n VIGOR: Interactive Visual Exploration of Graph Query Results.\n \n \n \n\n\n \n Pienta, R.; Hohman, F.; Endert, A.; Tamersoy, A.; Roundy, K. A.; Gates, C. S.; Navathe, S. B.; and Chau, D. H.\n\n\n \n\n\n\n IEEE Transactions on Visualization and Computer Graphics, 24(1): 215–225. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@article{pienta:18:vigor,\n  author    = {Robert Pienta and\n               Fred Hohman and\n               Alex Endert and\n               Acar Tamersoy and\n               Kevin A. Roundy and\n               Christopher S. Gates and\n               Shamkant B. Navathe and\n               Duen Horng Chau},\n  title     = {{VIGOR:} Interactive Visual Exploration of Graph Query Results},\n  journal   = {{IEEE} Transactions on Visualization and Computer Graphics},\n  volume    = {24},\n  number    = {1},\n  pages     = {215--225},\n  year      = {2018},\n  part = {Part III: Node-level Summaries}\n}\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n FACETS: Adaptive Local Exploration of Large Graphs.\n \n \n \n\n\n \n Pienta, R.; Kahng, M.; Lin, Z.; Vreeken, J.; Talukdar, P. P.; Abello, J.; Parameswaran, G.; and Chau, D. H.\n\n\n \n\n\n\n In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{pienta:17:facets,\n  author    = {Robert Pienta and\n               Minsuk Kahng and\n               Zhiyuan Lin and\n               Jilles Vreeken and\n               Partha P. Talukdar and\n               James Abello and\n               Ganesh Parameswaran and\n               Duen Horng Chau},\n  title     = {{FACETS:} Adaptive Local Exploration of Large Graphs},\n  booktitle = {Proceedings of the 17th SIAM International Conference on Data Mining (SDM)},\n  year      = {2017},\n  part = {Part III: Node-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Mining Connection Pathways for Marked Nodes in Large Graphs.\n \n \n \n\n\n \n Akoglu, L.; Vreeken, J.; Tong, H.; Tatti, N.; and Faloutsos, C.\n\n\n \n\n\n\n In Proceedings of the 13th SIAM International Conference on Data Mining (SDM), 2013. SIAM\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n
@inproceedings{akoglu:13:dot2dot,\n  author = {Leman Akoglu and Jilles Vreeken and Hanghang Tong and Nikolaj Tatti and Christos Faloutsos},\n  title = {Mining Connection Pathways for Marked Nodes in Large Graphs},\n  booktitle = {Proceedings of the 13th SIAM International Conference on Data Mining (SDM)},\n  publisher = {SIAM},\n  year = {2013},\n  part = {Part III: Node-level Summaries}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n\n\n\n
\n\n\n \n\n \n \n \n \n\n
\n"}; document.write(bibbase_data.data);