{"type":"ScholarlyArticle","title":"Uncovering the Largest Community in Social Networks at Scale","authors":[{"name":"Shohei Matsugu","slug":"shohei-matsugu","given":"Shohei","family":"Matsugu","affiliation":"Graduate School of Science and Technology , University of Tsukuba , Japan"},{"name":"Yasuhiro Fujiwara","slug":"yasuhiro-fujiwara","given":"Yasuhiro","family":"Fujiwara","affiliation":"NTT Communication Science Laboratories , Japan"},{"name":"Hiroaki Shiokawa","slug":"hiroaki-shiokawa","given":"Hiroaki","family":"Shiokawa","affiliation":"Center for Computational Sciences , University of Tsukuba , Japan"}],"abstract":"The Maximum k-Plex Search (MPS) can find the largest k-plex, which is a generalization of the largest clique.\r\nAlthough MPS is commonly used in AI to effectively discover real-world communities of social networks, existing MPS algorithms suffer from high computational costs because they iteratively scan numerous nodes to find the largest k-plex.\r\nHere, we present an efficient MPS algorithm called Branch-and-Merge (BnM), which outputs an exact maximum k-plex.\r\nBnM merges unnecessary nodes to explore a smaller graph than the original one.\r\nExtensive evaluations on real-world social networks demonstrate that BnM significantly outperforms other state-of-the-art MPS algorithms in terms of running time.","doi":"10.24963/ijcai.2023/250","url":"https://ijcai.org/proceedings/2023/250","pdf":"https://ijcai.org/proceedings/2023/0250.pdf","markdown":"https://ijcai.org/proceedings/2023/250.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/250","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Data Mining","track":"Main Track","number":250,"pages":{"first":2251,"last":2260},"keywords":["Data Mining: DM: Mining text, web, social media","Data Mining: DM: Applications"],"videos":[],"references":[{"position":1,"raw":"[Abello et al., 2002] James Abello, Mauricio G. 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