{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T19:05:22Z","timestamp":1778267122705,"version":"3.51.4"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72303183"],"award-info":[{"award-number":["72303183"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71873108"],"award-info":[{"award-number":["71873108"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072379"],"award-info":[{"award-number":["62072379"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Laboratory of Financial Intelligence and Financial Engineering of Sichuan Province"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1109\/tkde.2023.3310592","type":"journal-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T17:41:20Z","timestamp":1693503680000},"page":"1698-1712","source":"Crossref","is-referenced-by-count":19,"title":["Learning to Understand the Vague Graph for Stock Prediction With Momentum Spillovers"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4553-8464","authenticated-orcid":false,"given":"Rong","family":"Xing","sequence":"first","affiliation":[{"name":"Fintech Innovation Center, Southwestern University of Finance and Economics, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0698-9302","authenticated-orcid":false,"given":"Rui","family":"Cheng","sequence":"additional","affiliation":[{"name":"Fintech Innovation Center, Southwestern University of Finance and Economics, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2382-1522","authenticated-orcid":false,"given":"Jiwen","family":"Huang","sequence":"additional","affiliation":[{"name":"Fintech Innovation Center, Southwestern University of Finance and Economics, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3209-0149","authenticated-orcid":false,"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"Fintech Innovation Center, Southwestern University of Finance and Economics, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4436-3308","authenticated-orcid":false,"given":"Jingmei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Fintech Innovation Center, Southwestern University of Finance and Economics, Chengdu, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfineco.2019.10.007"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3269269"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/626"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3309547"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2021.3079496"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/529"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1002\/int.22950"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3386\/w25398"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1080\/1540496X.2019.1695597"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"ref12","article-title":"Gated graph sequence neural networks","volume-title":"Proc. 4th Int. Conf. Learn. Representations","author":"Li"},{"key":"ref13","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. 5th Int. Conf. Learn. Representations","author":"Kipf"},{"key":"ref14","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref15","article-title":"Graph attention networks","volume-title":"Proc. 6th Int. Conf. Learn. Representations","author":"Velivckovic"},{"key":"ref16","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","volume-title":"Proc. 6th Int. Conf. Learn. Representations","author":"Li"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107000"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/505"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/0304-405X(93)90023-5"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.2007.01232.x"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.2006.00831.x"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.2004.00662.x"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfineco.2018.11.009"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfineco.2014.10.010"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.2307\/2977928"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1111\/jofi.12122"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1111\/jofi.12149"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-6261.2008.01379.x"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfineco.2021.08.017"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.1998.725072"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2006.115"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2016.03.001"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/1462198.1462204"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/d14-1148"},{"key":"ref36","first-page":"2327","article-title":"Deep learning for event-driven stock prediction","volume-title":"Proc. 24th Int. Joint Conf. Artif. Intell.","author":"Ding"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098117"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfineco.2018.11.008"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1093\/rfs\/hhz145"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16077"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3090769"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3027642"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2017.2741444"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20369"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.3905\/jpm.2015.42.1.013"},{"key":"ref46","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Statist.","author":"Glorot"},{"key":"ref47","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Kingma"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2968894"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/10462568\/10236457.pdf?arnumber=10236457","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T18:31:08Z","timestamp":1725647468000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10236457\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4]]},"references-count":48,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2023.3310592","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4]]}}}