{"type":"ScholarlyArticle","title":"TAXOGAN: Hierarchical Network Representation Learning via Taxonomy Guided Generative Adversarial Networks (Extended Abstract)","authors":[{"name":"Carl Yang","slug":"carl-yang","given":"Carl","family":"Yang","affiliation":""},{"name":"Jieyu Zhang","slug":"jieyu-zhang","given":"Jieyu","family":"Zhang","affiliation":""},{"name":"Jiawei Han","slug":"jiawei-han","given":"Jiawei","family":"Han","affiliation":""}],"abstract":"Network representation learning aims at transferring node proximity in networks into distributed vectors, which can be leveraged in various downstream applications. Recent research has shown that nodes in a network can often be organized in latent hierarchical structures, but without a particular underlying taxonomy, the learned node embedding is less useful nor interpretable. In this work, we aim to improve network embedding by modeling the conditional node proximity in networks indicated by node labels residing in real taxonomies. In the meantime, we also aim to model the hierarchical label proximity in the given taxonomies, which is too coarse by solely looking at the hierarchical topologies. Comprehensive experiments and case studies demonstrate the utility of TAXOGAN.","doi":"10.24963/ijcai.2021/666","url":"https://ijcai.org/proceedings/2021/666","pdf":"https://ijcai.org/proceedings/2021/0666.pdf","markdown":"https://ijcai.org/proceedings/2021/666.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/666","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Sister Conferences Best Papers","track":"Sister Conferences Best Papers","number":666,"pages":{"first":4859,"last":4863},"keywords":["Data Mining: Mining Graphs, Semi Structured Data, Complex Data","Knowledge Representation and Reasoning: Leveraging Knowledge and Learning","Machine Learning: Knowledge Aided Learning","Machine Learning Applications: Networks"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}