{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T17:05:14Z","timestamp":1774717514880,"version":"3.50.1"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3361284","type":"journal-article","created":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T18:48:40Z","timestamp":1706813320000},"page":"20490-20508","source":"Crossref","is-referenced-by-count":4,"title":["On the Use of Spatial Graphs for Performance Degradation Root-Cause Analysis Toward Self-Healing Mobile Networks"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4572-9156","authenticated-orcid":false,"given":"Lu\u00eds","family":"Mata","sequence":"first","affiliation":[{"name":"Instituto de Telecomunica&#x00E7;&#x00F5;es, Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2471-170X","authenticated-orcid":false,"given":"Marco","family":"Sousa","sequence":"additional","affiliation":[{"name":"Instituto Superior de Engenharia de Lisboa, Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0279-8741","authenticated-orcid":false,"given":"Pedro","family":"Vieira","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica&#x00E7;&#x00F5;es, Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0266-4022","authenticated-orcid":false,"given":"Maria Paula","family":"Queluz","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica&#x00E7;&#x00F5;es, Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2115-7245","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica&#x00E7;&#x00F5;es, Lisbon, Portugal"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/icbaie52039.2021.9390061"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/gcwkshps52748.2021.9681937"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/wcnc51071.2022.9771947"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.34133\/2022\/9758169"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/eucnc48522.2020.9200928"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tnsm.2021.3095463"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3100155"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/vtc2022-spring54318.2022.9860734"},{"key":"ref9","volume-title":"Understanding Deep Learning","author":"Prince","year":"2023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2020.2978386"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/access.2022.3193486"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/access.2022.3217912"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/wimob50308.2020.9253369"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/icc.2017.7997286"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/jsac.2019.2927068"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/apsipaasc47483.2019.9023112"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/comst.2021.3063822"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/globecom46510.2021.9685185"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/vts50974.2021.9441030"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/noms56928.2023.10154218"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ccisp55629.2022.9974518"},{"key":"ref22","article-title":"Consistent individualized feature attribution for tree ensembles","author":"Lundberg","year":"2018","journal-title":"arXiv:1802.03888"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/twc.2022.3219840"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ciss50987.2021.9400216"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/urucon53396.2021.9647374"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411983"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2021.3081010"},{"key":"ref28","article-title":"Self-attention graph pooling","author":"Lee","year":"2019","journal-title":"arXiv:1904.08082"},{"key":"ref29","first-page":"668","article-title":"Spatial graph convolutional networks","volume-title":"Proc. 27th Int. Conf. ICONIP","author":"Spurek"},{"key":"ref30","first-page":"1","article-title":"Positional encoder graph neural networks for geographic data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Klemmer"},{"key":"ref31","first-page":"1","article-title":"Geom-GCN: Geometric graph convolutional networks","volume-title":"Proc. 8th Int. Conf. Learn. Represent. (ICLR)","author":"Pei"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tmc.2021.3129796"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/tits.2022.3208952"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/lcomm.2021.3138075"},{"key":"ref35","article-title":"Captum: A unified and generic model interpretability library for PyTorch","author":"Kokhlikyan","year":"2020","journal-title":"arXiv:2009.07896"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.01.079"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32520-6_22"},{"key":"ref38","first-page":"1","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Represent. (ICLR)","author":"Kingma"},{"key":"ref39","article-title":"Deep learning using rectified linear units (ReLU)","author":"Fred Agarap","year":"2018","journal-title":"arXiv:1803.08375"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/yac.2019.8787645"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-41136-6_5"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1810.11363"},{"key":"ref46","first-page":"1","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ke"},{"key":"ref47","article-title":"Network performance enhancement by implementing self-healing functions in mobile network operations","author":"Cil\u00ednio","year":"2022"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/eucnc.2014.6882629"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10418212.pdf?arnumber=10418212","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T18:51:57Z","timestamp":1731696717000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10418212\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3361284","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}