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However, learning an optimal SBM for a given network is an NP-hard problem. This results in significant limitations when it comes to applications of SBMs in large-scale networks, because of the significant computational overhead of existing SBM models, as well as their learning methods. Reducing the cost of SBM learning and making it scalable for handling large-scale networks, while maintaining the good theoretical properties of SBM, remains an unresolved problem. In this work, we address this challenging task from a novel perspective of model redefinition. We propose a novel redefined SBM with Poisson distribution and its block-wise learning algorithm that can efficiently analyse large-scale networks. Extensive validation conducted on both artificial and real-world data shows that our proposed method significantly outperforms the state-of-the-art methods in terms of a reasonable trade-off between accuracy and scalability.\n            <jats:sup>1<\/jats:sup>\n          <\/jats:p>","DOI":"10.1145\/3442589","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T15:42:54Z","timestamp":1619019774000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["A Scalable Redefined Stochastic Blockmodel"],"prefix":"10.1145","volume":"15","author":[{"given":"Xueyan","family":"Liu","sequence":"first","affiliation":[{"name":"Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Yang","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hechang","family":"Chen","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katarzyna","family":"Musial","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxu","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Technology Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[{"name":"Aviation University of Air Force and Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanli","family":"Zuo","sequence":"additional","affiliation":[{"name":"Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/3122009.3242034"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the 3rd International Workshop on Link Discovery. 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