{"type":"ScholarlyArticle","title":"Scalable Graph Classification via Random Walk Fingerprints (Extended Abstract)","authors":[{"name":"Peiyan Li","slug":"peiyan-li","given":"Peiyan","family":"Li","affiliation":""},{"name":"Honglian Wang","slug":"honglian-wang","given":"Honglian","family":"Wang","affiliation":""},{"name":"Christian Böhm","slug":"christian-bohm","given":"Christian","family":"Böhm","affiliation":""}],"abstract":"We design a lightweight structural feature extraction technique for graph classification. It leverages node subsets and connection strength reflected by random-walk-based heuristics, presenting a scalable, unsupervised, and easily interpretable alternative. We provide theoretical insights into our technical design and establish a relation between the extracted structural features and the graph spectrum. We show our method achieves high levels of computational efficiency while maintaining robust classification accuracy.","doi":"10.24963/ijcai.2025/1215","url":"https://ijcai.org/proceedings/2025/1215","pdf":"https://ijcai.org/proceedings/2025/1215.pdf","markdown":"https://ijcai.org/proceedings/2025/1215.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/1215","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Sister Conferences Best Papers","track":"Sister Conferences Best Papers","number":1215,"pages":{"first":10912,"last":10915},"keywords":["Sister Conferences Best Papers: Data Mining"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}