{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:58:24Z","timestamp":1772265504675,"version":"3.50.1"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030185787","type":"print"},{"value":"9783030185794","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-18579-4_30","type":"book-chapter","created":{"date-parts":[[2019,4,23]],"date-time":"2019-04-23T15:05:36Z","timestamp":1556031936000},"page":"502-518","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Dynamic Stochastic Block Model with Scale-Free Characteristic for Temporal Complex Networks"],"prefix":"10.1007","author":[{"given":"Xunxun","family":"Wu","sequence":"first","affiliation":[]},{"given":"Pengfei","family":"Jiao","sequence":"additional","affiliation":[]},{"given":"Yaping","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Tianpeng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Wenjun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,4,24]]},"reference":[{"key":"30_CR1","unstructured":"Airoldi, E.M., Blei, D.M., Fienberg, S.E., Xing, E.P., Jaakkola, T.: Mixed membership stochastic block models for relational data with application to protein-protein interactions. In: Proceedings of the International Biometrics Society Annual Meeting, vol. 15 (2006)"},{"issue":"8","key":"30_CR2","doi-asserted-by":"publisher","first-page":"1838","DOI":"10.1109\/TKDE.2013.131","volume":"26","author":"F Folino","year":"2014","unstructured":"Folino, F., Pizzuti, C.: An evolutionary multiobjective approach for community discovery in dynamic networks. IEEE Trans. Knowl. Data Eng. 26(8), 1838\u20131852 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"30_CR3","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-69942-4","volume-title":"Machine Learning for Multimedia Content Analysis","author":"Y Gong","year":"2007","unstructured":"Gong, Y., Xu, W.: Machine Learning for Multimedia Content Analysis, vol. 30. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-0-387-69942-4"},{"key":"30_CR4","doi-asserted-by":"crossref","unstructured":"Greene, D., Doyle, D., Cunningham, P.: Tracking the evolution of communities in dynamic social networks. In: 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 176\u2013183. IEEE (2010)","DOI":"10.1109\/ASONAM.2010.17"},{"issue":"2","key":"30_CR5","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/0378-8733(83)90021-7","volume":"5","author":"PW Holland","year":"1983","unstructured":"Holland, P.W., Laskey, K.B., Leinhardt, S.: Stochastic blockmodels: first steps. Soc. Netw. 5(2), 109\u2013137 (1983)","journal-title":"Soc. Netw."},{"key":"30_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2307\/270703","volume":"7","author":"PW Holland","year":"1976","unstructured":"Holland, P.W., Leinhardt, S.: Local structure in social networks. Sociol. Methodol. 7, 1\u201345 (1976)","journal-title":"Sociol. Methodol."},{"issue":"suppl 1","key":"30_CR7","doi-asserted-by":"publisher","first-page":"5249","DOI":"10.1073\/pnas.0307750100","volume":"101","author":"J Hopcroft","year":"2004","unstructured":"Hopcroft, J., Khan, O., Kulis, B., Selman, B.: Tracking evolving communities in large linked networks. Proc. Natl. Acad. Sci. 101(suppl 1), 5249\u20135253 (2004)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"30_CR8","doi-asserted-by":"crossref","unstructured":"Jin, D., Chen, Z., He, D., Zhang, W.: Modeling with node degree preservation can accurately find communities. In: AAAI, pp. 160\u2013167 (2015)","DOI":"10.1609\/aaai.v29i1.9201"},{"key":"30_CR9","doi-asserted-by":"crossref","unstructured":"Jin, D., Wang, H., Dang, J., He, D., Zhang, W.: Detect overlapping communities via ranking node popularities. In: AAAI, pp. 172\u2013178 (2016)","DOI":"10.1609\/aaai.v30i1.9981"},{"key":"30_CR10","unstructured":"Jutla, I.S., Jeub, L.G., Mucha, P.J.: A generalized Louvain method for community detection implemented in matlab (2011). http:\/\/netwiki.amath.unc.edu\/GenLouvain"},{"issue":"1","key":"30_CR11","doi-asserted-by":"publisher","first-page":"016107","DOI":"10.1103\/PhysRevE.83.016107","volume":"83","author":"B Karrer","year":"2011","unstructured":"Karrer, B., Newman, M.E.: Stochastic blockmodels and community structure in networks. Phys. Rev. E 83(1), 016107 (2011)","journal-title":"Phys. Rev. E"},{"key":"30_CR12","doi-asserted-by":"crossref","unstructured":"Lee, P., Lakshmanan, L.V., Milios, E.E.: Incremental cluster evolution tracking from highly dynamic network data. In: 2014 IEEE 30th International Conference on Data Engineering (ICDE), pp. 3\u201314. IEEE (2014)","DOI":"10.1109\/ICDE.2014.6816635"},{"key":"30_CR13","doi-asserted-by":"crossref","unstructured":"Lin, Y.R., Chi, Y., Zhu, S., Sundaram, H., Tseng, B.L.: FacetNet: a framework for analyzing communities and their evolutions in dynamic networks. In: Proceedings of the 17th international conference on World Wide Web, pp. 685\u2013694. ACM (2008)","DOI":"10.1145\/1367497.1367590"},{"key":"30_CR14","unstructured":"Liu, W., Saganowski, S., Kazienko, P., Cheong, S.A.: Using machine learning to predict the evolution of physics research. arXiv preprint arXiv:1810.12116 (2018)"},{"issue":"2","key":"30_CR15","first-page":"36","volume":"5","author":"X Tang","year":"2014","unstructured":"Tang, X., Yang, C.C.: Detecting social media hidden communities using dynamic stochastic blockmodel with temporal Dirichlet process. ACM Trans. Intell. Syst. Technol. (TIST) 5(2), 36 (2014)","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"},{"key":"30_CR16","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511815478","volume-title":"Social Network Analysis: Methods and Applications","author":"S Wasserman","year":"1994","unstructured":"Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications, vol. 8. Cambridge University Press, Cambridge (1994)"},{"key":"30_CR17","unstructured":"Wilson, J.D., Stevens, N.T., Woodall, W.H.: Modeling and detecting change in temporal networks via a dynamic degree corrected stochastic block model. arXiv preprint arXiv:1605.04049 (2016)"},{"key":"30_CR18","doi-asserted-by":"crossref","unstructured":"Xu, W., Gong, Y.: Document clustering by concept factorization. In: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 202\u2013209. ACM (2004)","DOI":"10.1145\/1008992.1009029"},{"issue":"2","key":"30_CR19","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s10994-010-5214-7","volume":"82","author":"T Yang","year":"2011","unstructured":"Yang, T., Chi, Y., Zhu, S., Gong, Y., Jin, R.: Detecting communities and their evolutions in dynamic social networks\u2013a Bayesian approach. Mach. Learn. 82(2), 157\u2013189 (2011)","journal-title":"Mach. Learn."},{"key":"30_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, G., Jin, D., Gao, J., Jiao, P., Fogelman-Souli\u00e9, F., Huang, X.: Finding communities with hierarchical semantics by distinguishing general and specialized topics. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence, pp. 3648\u20133654. AAAI Press (2018)","DOI":"10.24963\/ijcai.2018\/507"}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-18579-4_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T08:53:17Z","timestamp":1710233597000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-18579-4_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030185787","9783030185794"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-18579-4_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"24 April 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chiang Mai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/dasfaa2019.eng.cmu.ac.th\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"501","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"92","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"64","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"18% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13 demo papers, 6 tutorial papers","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}