{"type":"ScholarlyArticle","title":"A Survey on Network Alignment: Approaches, Applications and Future Directions","authors":[{"name":"Shruti Saxena","slug":"shruti-saxena","given":"Shruti","family":"Saxena","affiliation":"Indian Institute of Technology Patna , India"},{"name":"Joydeep Chandra","slug":"joydeep-chandra","given":"Joydeep","family":"Chandra","affiliation":"Indian Institute of Technology Patna , India"}],"abstract":"Network alignment, the task of mapping corresponding nodes across networks, is attracting more attention for cross-network analysis in diverse domains, including social, biological, and co-authorship networks. Although a variety of methods have been proposed, we lack a holistic understanding of the approaches and applications. Our survey aims to bridge this gap by first proposing a taxonomy of network alignment, characterizing existing approaches, and then systematically summarizing and reviewing their performance and highlighting their scopes for future development. Finally, we discuss some important applications and give directions for future research within this domain.","doi":"10.24963/ijcai.2024/908","url":"https://ijcai.org/proceedings/2024/908","pdf":"https://ijcai.org/proceedings/2024/0908.pdf","markdown":"https://ijcai.org/proceedings/2024/908.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/908","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Survey Track","track":"Survey Track","number":908,"pages":{"first":8216,"last":8224},"keywords":["Machine Learning: ML: Sequence and graph learning","Machine Learning: ML: Adversarial machine learning","Data Mining: DM: Applications","Data Mining: DM: Mining graphs","Machine Learning: ML: Representation learning","Knowledge Representation and Reasoning: KRR: Applications","Data Mining: DM: Networks","Machine Learning: ML: Applications","Machine Learning: ML: Active learning"],"videos":[],"references":[{"position":1,"raw":"[Almulhim et al., 2019] Aljohara Almulhim, Vachik S Dave, and Mohammad Al Hasan. 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