{"id":"https://openalex.org/W4416261150","doi":"https://doi.org/10.48550/arxiv.2506.22199","title":"REDELEX: A Framework for Relational Deep Learning Exploration","display_name":"REDELEX: A Framework for Relational Deep Learning Exploration","publication_year":2025,"publication_date":"2025-06-27","ids":{"openalex":"https://openalex.org/W4416261150","doi":"https://doi.org/10.48550/arxiv.2506.22199"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2506.22199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.22199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2506.22199","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115057035","display_name":"Jakub Pele\u0161ka","orcid":"https://orcid.org/0009-0000-8561-8106"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pele\u0161ka, Jakub","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070997427","display_name":"Gustav \u0160\u00edr","orcid":"https://orcid.org/0000-0001-6964-4232"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u0160\u00edr, Gustav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9248999953269958,"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":0.9248999953269958,"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":0.0215000007301569,"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/T11719","display_name":"Data Quality and Management","score":0.010999999940395355,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6492000222206116},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.5521000027656555},{"id":"https://openalex.org/keywords/relational-model","display_name":"Relational model","score":0.4447000026702881},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44369998574256897},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.44110000133514404},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.3774000108242035}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.732699990272522},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6492000222206116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5597000122070312},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.5521000027656555},{"id":"https://openalex.org/C40207289","wikidata":"https://www.wikidata.org/wiki/Q755662","display_name":"Relational model","level":3,"score":0.4447000026702881},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44369998574256897},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.44110000133514404},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.41620001196861267},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.3774000108242035},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35429999232292175},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C2780977526","wikidata":"https://www.wikidata.org/wiki/Q42417149","display_name":"Data exploration","level":3,"score":0.3165000081062317},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.29910001158714294},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26989999413490295},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2506.22199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.22199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2506.22199","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.22199","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Relational":[0,26],"databases":[1],"(RDBs)":[2],"are":[3,38],"widely":[4],"regarded":[5],"as":[6,32,40],"the":[7,44,67,70,77,80,100,113,124,134],"gold":[8],"standard":[9],"for":[10,92],"storing":[11],"structured":[12],"information.":[13],"Consequently,":[14],"predictive":[15],"tasks":[16],"leveraging":[17],"this":[18,84],"data":[19],"format":[20],"hold":[21],"significant":[22],"application":[23,45],"promise.":[24],"Recently,":[25],"Deep":[27],"Learning":[28],"(RDL)":[29],"has":[30],"emerged":[31],"a":[33,62],"novel":[34],"paradigm":[35],"wherein":[36],"RDBs":[37],"conceptualized":[39],"graph":[41,48],"structures,":[42],"enabling":[43],"of":[46,64,72,79,96,104,119,128],"various":[47,73],"neural":[49],"architectures":[50],"to":[51,112],"effectively":[52],"address":[53],"these":[54],"tasks.":[55],"However,":[56],"given":[57],"its":[58],"novelty,":[59],"there":[60],"is":[61],"lack":[63],"analysis":[65],"into":[66,133],"relationships":[68],"between":[69],"performance":[71,127],"RDL":[74,94,129],"models":[75,95],"and":[76,144],"characteristics":[78],"underlying":[81],"RDBs.":[82],"In":[83],"study,":[85],"we":[86,109,122],"present":[87],"REDELEX$-$a":[88],"comprehensive":[89],"exploration":[90],"framework":[91],"evaluating":[93],"varying":[97],"complexity":[98],"on":[99],"most":[101],"diverse":[102],"collection":[103],"over":[105],"70":[106],"RDBs,":[107],"which":[108],"make":[110],"available":[111],"community.":[114],"Benchmarked":[115],"alongside":[116],"key":[117],"representatives":[118],"classic":[120],"methods,":[121],"confirm":[123],"generally":[125],"superior":[126],"while":[130],"providing":[131],"insights":[132],"main":[135],"factors":[136],"shaping":[137],"performance,":[138],"including":[139],"model":[140],"complexity,":[141],"database":[142],"sizes":[143],"their":[145],"structural":[146],"properties.":[147]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
