{"id":"https://openalex.org/W7135169309","doi":"https://doi.org/10.1109/seeda-cecnsm68644.2025.11433191","title":"Lessons Learned from Setting Up Kubernetes for Operations on Temporal Graph Neural Networks","display_name":"Lessons Learned from Setting Up Kubernetes for Operations on Temporal Graph Neural Networks","publication_year":2025,"publication_date":"2025-09-19","ids":{"openalex":"https://openalex.org/W7135169309","doi":"https://doi.org/10.1109/seeda-cecnsm68644.2025.11433191"},"language":null,"primary_location":{"id":"doi:10.1109/seeda-cecnsm68644.2025.11433191","is_oa":false,"landing_page_url":"https://doi.org/10.1109/seeda-cecnsm68644.2025.11433191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129044175","display_name":"Fotis Sofoulis","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Fotis Sofoulis","raw_affiliation_strings":["CEID, University of Patras"],"raw_orcid":"https://orcid.org/0009-0007-0619-5231","affiliations":[{"raw_affiliation_string":"CEID, University of Patras","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044250636","display_name":"\u0393\u03b5\u03ce\u03c1\u03b3\u03b9\u03bf\u03c2 \u0394\u03c1\u03b1\u03ba\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2","orcid":"https://orcid.org/0000-0002-0975-1877"},"institutions":[{"id":"https://openalex.org/I4210094138","display_name":"University of West Attica","ror":"https://ror.org/00r2r5k05","country_code":"GR","type":"education","lineage":["https://openalex.org/I4210094138"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Georgios Drakopoulos","raw_affiliation_strings":["University of West Attica,ICE Department"],"raw_orcid":"https://orcid.org/0000-0002-0975-1877","affiliations":[{"raw_affiliation_string":"University of West Attica,ICE Department","institution_ids":["https://openalex.org/I4210094138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019293826","display_name":"Leonidas Theodorakopoulos","orcid":"https://orcid.org/0000-0002-0891-6780"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Leonidas Theodorakopoulos","raw_affiliation_strings":["University of Patras,DEPT Department"],"raw_orcid":"https://orcid.org/0000-0002-0891-6780","affiliations":[{"raw_affiliation_string":"University of Patras,DEPT Department","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129046156","display_name":"Spyros Sioutas","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Spyros Sioutas","raw_affiliation_strings":["CEID, University of Patras"],"raw_orcid":"https://orcid.org/0000-0003-1825-5565","affiliations":[{"raw_affiliation_string":"CEID, University of Patras","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82864411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.91839998960495,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.91839998960495,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.013199999928474426,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.007400000002235174,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4851999878883362},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42899999022483826},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2822999954223633},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.243599995970726},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.23280000686645508}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6495000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49639999866485596},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4851999878883362},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27570000290870667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.243599995970726},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.23280000686645508},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.22100000083446503}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/seeda-cecnsm68644.2025.11433191","is_oa":false,"landing_page_url":"https://doi.org/10.1109/seeda-cecnsm68644.2025.11433191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2739003666","https://openalex.org/W2904503978","https://openalex.org/W3111344851","https://openalex.org/W4206222751","https://openalex.org/W4281381223","https://openalex.org/W4404315101","https://openalex.org/W4404734757","https://openalex.org/W4405082965","https://openalex.org/W4405220634","https://openalex.org/W4406457883","https://openalex.org/W4407128748","https://openalex.org/W4407196290","https://openalex.org/W4407784074","https://openalex.org/W4407932729","https://openalex.org/W4408078238","https://openalex.org/W4408310750","https://openalex.org/W4408429364","https://openalex.org/W4408435165","https://openalex.org/W4408673182","https://openalex.org/W4409097566","https://openalex.org/W4409197411","https://openalex.org/W4409361893","https://openalex.org/W4409364019","https://openalex.org/W4409446028","https://openalex.org/W4410197254","https://openalex.org/W4410274379","https://openalex.org/W4411019646","https://openalex.org/W4411026330","https://openalex.org/W4411201709","https://openalex.org/W4411350353"],"related_works":[],"abstract_inverted_index":{"Infrastructure":[0],"is":[1,34,74,114,118],"one":[2,75],"of":[3,6,15,27,57],"the":[4,13,16,25,28,41,84,110],"mainstays":[5],"contemporary":[7],"deep":[8],"learning":[9],"as":[10,22,24,48],"it":[11,138],"determines":[12],"size":[14],"data":[17],"which":[18,113],"can":[19],"be":[20],"stored":[21],"well":[23],"efficiency":[26],"operations":[29,51,59],"performed":[30],"on":[31,122],"them.":[32],"This":[33,82],"especially":[35],"true":[36],"in":[37,61,116],"graph-based":[38],"methods":[39],"where":[40],"conventional":[42],"table-oriented":[43],"setup":[44],"does":[45],"not":[46],"apply,":[47],"most":[49],"graph":[50,67,98],"translate":[52],"to":[53,78,119],"a":[54,87,96],"considerable":[55,62],"number":[56],"join":[58],"resulting":[60],"complexity.":[63],"Graph":[64],"databases":[65],"and":[66,102,124,128,133,150],"processing":[68],"tools":[69],"deployed":[70,90],"over":[71,91],"distributed":[72],"infrastructure":[73],"efficient":[76],"way":[77],"address":[79],"this":[80],"issue.":[81],"was":[83],"case":[85],"with":[86],"Neo4j":[88],"instance":[89],"Apache":[92],"Spark":[93],"for":[94],"storing":[95],"temporal":[97],"neural":[99],"network":[100],"(TGNN)":[101],"performing":[103],"community":[104],"structure":[105],"discovery.":[106],"The":[107,142],"motivation":[108],"behind":[109],"proposed":[111],"infrastructure,":[112],"described":[115],"detail,":[117],"rely":[120],"exclusively":[121],"standard":[123],"readily":[125],"available":[126],"hardware":[127],"networking":[129],"equipment.":[130],"Furthermore,":[131],"implications":[132],"experience":[134],"gained":[135],"while":[136],"setting":[137],"up":[139],"are":[140],"explained.":[141],"latter":[143],"includes":[144],"lessons":[145],"about":[146],"storage":[147],"allocation,":[148],"networking,":[149],"package":[151],"dependencies.":[152]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-14T00:00:00"}