{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T18:57:05Z","timestamp":1769713025317,"version":"3.49.0"},"reference-count":14,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,1,30]]},"abstract":"<jats:p>Role-oriented network embedding aims to preserve the structural similarity of nodes so that nodes with the same role stay close to each other in the embedding space. Role-oriented network embeddings have wide applications such as electronic business and scientific discovery. Anonymous walk (AW) has a powerful ability to capture structural information of nodes, but at present, there are few role-oriented network embedding methods based on AW. Our main contribution is the proposal of a new framework named REAW, which can generate the role-oriented embeddings of nodes based on anonymous walks. We first partition a number of anonymous walks starting from a node into the representative set and the non-representative set. Then, we leverage contrastive learning techniques to learn AW embeddings. We integrate the learned AW embeddings with AW\u2019s empirical distribution to obtain the structural feature of the node, and finally we generate the node\u2019s embedding through message passing operations. Extensive experiments on real network datasets demonstrate the effectiveness of our framework in capturing the role of nodes.<\/jats:p>","DOI":"10.3233\/jifs-222712","type":"journal-article","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T11:37:57Z","timestamp":1667561877000},"page":"2729-2739","source":"Crossref","is-referenced-by-count":0,"title":["Role-oriented network embedding via anonymous walks"],"prefix":"10.1177","volume":"44","author":[{"given":"Yutan","family":"Qiu","sequence":"first","affiliation":[{"name":"College of Computer Science, Chongqing University, Chongqing, China"}]},{"given":"Qing","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer Science, Chongqing University, Chongqing, China"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-222712_ref7","unstructured":"Will Hamilton , Zhitao Ying , Jure Leskovec , Inductive representation learning on large graphs, Advances in neural information processing systems, 30, 2017."},{"issue":"8","key":"10.3233\/JIFS-222712_ref11","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Sepp Hochreiter","year":"1997","journal-title":"Neural Computation"},{"key":"10.3233\/JIFS-222712_ref13","doi-asserted-by":"crossref","unstructured":"Yilun Jin , Guojie Song , Chuan Shi , Gralsp: Graph neural networks with local structural patterns, In volume pages, Proceedings of the AAAI Conference on Artificial Intelligence 34 (2020).","DOI":"10.1609\/aaai.v34i04.5861"},{"issue":"1","key":"10.3233\/JIFS-222712_ref18","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1080\/0022250X.1971.9989788","article-title":"Structural equivalence of individuals in social networks","volume":"1","author":"Francois Lorrain","year":"1971","journal-title":"The Journal of Mathematical Sociology"},{"issue":"1","key":"10.3233\/JIFS-222712_ref20","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1145\/1111322.1111328","article-title":"The internet as-level topology: three data sources and one definitive metric","volume":"36","author":"Priya Mahadevan","year":"2006","journal-title":"ACM SIGCOMM Computer Communication Review"},{"key":"10.3233\/JIFS-222712_ref21","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.dam.2015.06.035","article-title":"and , Reconstructing markov processes from independent and anonymous experiments","volume":"200","author":"Silvio Micali","year":"2016","journal-title":"Discrete Applied Mathematics"},{"issue":"2","key":"10.3233\/JIFS-222712_ref25","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1007\/s40747-021-00580-x","article-title":"Applications of graph\u2019s complete degree with bipolar fuzzy information","volume":"8","author":"Soumitra Poulik","year":"2022","journal-title":"Complex & Intelligent Systems"},{"issue":"5","key":"10.3233\/JIFS-222712_ref31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3397191","article-title":"On proximity and structural role-based embeddings in networks: Misconceptions, techniques, and applications","volume":"14","author":"Ryan Rossi","year":"2020","journal-title":"ACM Transactions on Knowledge Discovery from Data (TKDD)"},{"key":"10.3233\/JIFS-222712_ref32","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","article-title":"Silhouettes: a graphical aid to the interpretation and validation of cluster analysis","volume":"20","author":"Peter Ahmed","year":"1987","journal-title":"Journal of Computational and Applied Mathematics"},{"key":"10.3233\/JIFS-222712_ref33","unstructured":"Nino Shervashidze , Pascal Schweitzer, , Erik Jan Van Leeuwen , Kurt Mehlhorn , Karsten M. Borgwardt , Weisfeiler-lehman graph kernels, Journal of Machine Learning Research 12(9) (2011)."},{"key":"10.3233\/JIFS-222712_ref35","doi-asserted-by":"crossref","first-page":"106124","DOI":"10.1109\/ACCESS.2019.2932396","article-title":"Unifying structural proximity and equivalence for network embedding","volume":"7","author":"Benyun Shi","year":"2019","journal-title":"IEEE Access"},{"key":"10.3233\/JIFS-222712_ref38","first-page":"20","article-title":"Graph attention networks","volume":"1050","author":"Petar Velickovic","year":"2017","journal-title":"Stat"},{"key":"10.3233\/JIFS-222712_ref40","doi-asserted-by":"crossref","first-page":"107021","DOI":"10.1016\/j.knosys.2021.107021","article-title":"Learning flexible network representation via anonymous walks","volume":"222","author":"Yu Wang","year":"2021","journal-title":"Knowledge-Based Systems"},{"issue":"14","key":"10.3233\/JIFS-222712_ref44","doi-asserted-by":"crossref","first-page":"i190","DOI":"10.1093\/bioinformatics\/btx252","article-title":"Predicting multicellular function through multi-layer tissue networks","volume":"33","author":"Marinka Zitnik","year":"2017","journal-title":"Bioinformatics"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-222712","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T06:58:01Z","timestamp":1769669881000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-222712"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,30]]},"references-count":14,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.3233\/jifs-222712","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,30]]}}}