{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T01:02:56Z","timestamp":1768352576849,"version":"3.49.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2019JJ40340"],"award-info":[{"award-number":["2019JJ40340"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701502"],"award-info":[{"award-number":["61701502"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1109\/tnnls.2020.3027687","type":"journal-article","created":{"date-parts":[[2020,10,16]],"date-time":"2020-10-16T19:31:50Z","timestamp":1602876710000},"page":"292-303","source":"Crossref","is-referenced-by-count":9,"title":["An R-Convolution Graph Kernel Based on Fast Discrete-Time Quantum Walk"],"prefix":"10.1109","volume":"33","author":[{"given":"Yi","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6796-2533","authenticated-orcid":false,"given":"Lulu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7265-3033","authenticated-orcid":false,"given":"Richard C.","family":"Wilson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.10.029"},{"issue":"7","key":"ref2","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1023\/A:1021271615909","article-title":"Maximum common subgraph isomorphism algorithms for the matching of chemical structures","volume":"16","author":"Raymond","year":"2002","journal-title":"J. Comput. Aided Mol. Des."},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2274576.2274578"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00382-0_44"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-008-5086-2"},{"key":"ref6","first-page":"1","article-title":"A unifying view of explicit and implicit feature maps for structured data: Systematic studies of graph kernels","volume":"abs\/1703.00676","author":"Kriege","year":"2017","journal-title":"CoRR"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(97)00060-3"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.22"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-45167-9_11"},{"key":"ref10","first-page":"2539","article-title":"Weisfeiler-Lehman graph kernels","volume":"12","author":"Shervashidze","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref11","first-page":"30","article-title":"An aligned subtree kernel for weighted graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bai"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2248093"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevA.48.1687"},{"key":"ref14","article-title":"Convolution kernels on discrete structures","author":"Haussler","year":"1999"},{"key":"ref15","article-title":"Information theoretic graph kernels","author":"Bai","year":"2014"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2005.132"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0142"},{"key":"ref18","first-page":"3964","article-title":"RetGK: Graph kernels based on return probabilities of random walks","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref19","first-page":"2990","article-title":"The multiscale Laplacian graph kernel","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Kondor"},{"key":"ref20","first-page":"1","article-title":"A graph kernel based on the Jensen-Shannon representation alignment","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Bai"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/360"},{"key":"ref22","first-page":"488","article-title":"Efficient graphlet kernels for large graph comparison","volume-title":"Proc. Artif. Intell. Statist.","author":"Shervashidze"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783417"},{"key":"ref24","first-page":"291","article-title":"Subgraph matching kernels for attributed graphs","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kriege"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2756836"},{"key":"ref26","first-page":"1623","article-title":"On valid optimal assignment kernels and applications to graph classification","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Kriege"},{"key":"ref27","first-page":"678","article-title":"Graph invariant kernels","volume-title":"Proc. AAAI Conf. Artif. Intell. (AAAI)","author":"Orsini"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/e21030328"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-38221-5_13"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-38221-5_11"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.91.022815"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2016.08.019"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44848-9_7"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.09.001"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-23231-7_3"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.10.025"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2014.665"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s11128-010-0205-y"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s00020-009-1680-3"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0186"},{"key":"ref41","first-page":"2014","article-title":"Learning convolutional neural networks for graphs","volume-title":"Proc. ICML","author":"Niepert"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11782"},{"key":"ref43","volume-title":"Benchmark data sets for graph kernels","author":"Kersting","year":"2016"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3390\/e20120984"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3379500"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9670432\/09228895.pdf?arnumber=9228895","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:59:59Z","timestamp":1704844799000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9228895\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1]]},"references-count":45,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2020.3027687","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1]]}}}