{"id":"https://openalex.org/W3173587790","doi":"https://doi.org/10.1145/3448016.3457321","title":"ARM-Net: Adaptive Relation Modeling Network for Structured Data","display_name":"ARM-Net: Adaptive Relation Modeling Network for Structured Data","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3173587790","doi":"https://doi.org/10.1145/3448016.3457321","mag":"3173587790"},"language":"en","primary_location":{"id":"doi:10.1145/3448016.3457321","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457321","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457321","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457321","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shaofeng Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Shaofeng Cai","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kaiping Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kaiping Zheng","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"H. V. Jagadish","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. V. Jagadish","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Beng Chin Ooi","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Beng Chin Ooi","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":null,"display_name":"Meihui Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meihui Zhang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":3.0798,"has_fulltext":true,"cited_by_count":32,"citation_normalized_percentile":{"value":0.92775035,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9994000196456909,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9994000196456909,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973999857902527,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9962999820709229,"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/relation","display_name":"Relation (database)","score":0.6371999979019165},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5734999775886536},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5512999892234802},{"id":"https://openalex.org/keywords/structured-prediction","display_name":"Structured prediction","score":0.5105999708175659},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48919999599456787},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.448199987411499},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.44690001010894775},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.42579999566078186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7973999977111816},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6371999979019165},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5734999775886536},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5512999892234802},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5501999855041504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5414999723434448},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.5105999708175659},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48919999599456787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.460999995470047},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.44690001010894775},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.42579999566078186},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C40207289","wikidata":"https://www.wikidata.org/wiki/Q755662","display_name":"Relational model","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C38764148","wikidata":"https://www.wikidata.org/wiki/Q17098245","display_name":"Interaction information","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3448016.3457321","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457321","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457321","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2107.01830","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.01830","pdf_url":"https://arxiv.org/pdf/2107.01830","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3448016.3457321","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457321","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457321","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2184854824","display_name":null,"funder_award_id":"1934565","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3710419309","display_name":null,"funder_award_id":"1741022","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6748694274","display_name":null,"funder_award_id":"62050099","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7495556737","display_name":null,"funder_award_id":"1741022 and 1934565","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3173587790.pdf","grobid_xml":"https://content.openalex.org/works/W3173587790.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W183625566","https://openalex.org/W1983874169","https://openalex.org/W2160821628","https://openalex.org/W2193413348","https://openalex.org/W2194775991","https://openalex.org/W2247380138","https://openalex.org/W2265846598","https://openalex.org/W2282821441","https://openalex.org/W2475334473","https://openalex.org/W2509235963","https://openalex.org/W2517540742","https://openalex.org/W2525739395","https://openalex.org/W2563724055","https://openalex.org/W2604662567","https://openalex.org/W2610751324","https://openalex.org/W2690721124","https://openalex.org/W2743231118","https://openalex.org/W2767786571","https://openalex.org/W2793768763","https://openalex.org/W2806031239","https://openalex.org/W2948405945","https://openalex.org/W2962689739","https://openalex.org/W2962772482","https://openalex.org/W2962858109","https://openalex.org/W2963095307","https://openalex.org/W2963178695","https://openalex.org/W2963323306","https://openalex.org/W2963924287","https://openalex.org/W2964052347","https://openalex.org/W2964182926","https://openalex.org/W2965211237","https://openalex.org/W3029016840","https://openalex.org/W3031182173","https://openalex.org/W3038576231","https://openalex.org/W3177494680"],"related_works":[],"abstract_inverted_index":{"Relational":[0],"databases":[1],"are":[2,55],"the":[3,99,110,170,179,200,204,230],"de":[4],"facto":[5],"standard":[6],"for":[7,112,115,138,149,186,235,238,262],"storing":[8],"and":[9,13,57,67,141,165,176,182,241,257],"querying":[10],"structured":[11,17,48,139],"data,":[12,140],"extracting":[14],"insights":[15],"from":[16],"data":[18,33,151],"requires":[19],"advanced":[20],"analytics.":[21,152],"Deep":[22],"neural":[23],"networks":[24],"(DNNs)":[25],"have":[26],"achieved":[27],"super-human":[28],"prediction":[29,237],"performance":[30],"in":[31,64,104],"particular":[32],"types,":[34],"e.g.,":[35],"images.":[36],"However,":[37],"existing":[38,255],"DNNs":[39],"may":[40],"not":[41,70],"produce":[42],"meaningful":[43],"results":[44],"when":[45],"applied":[46],"to":[47,96,124,157,197],"data.":[49],"The":[50,83,153],"reason":[51],"is":[52,90,156],"that":[53,75,208,251],"there":[54],"correlations":[56],"dependencies":[58],"across":[59],"combinations":[60],"of":[61,85,101,122,215],"attribute":[62],"values":[63],"a":[65,81,142,192],"table,":[66],"these":[68],"do":[69],"follow":[71],"simple":[72],"additive":[73],"patterns":[74],"can":[76,210,228],"be":[77],"easily":[78],"mimicked":[79],"by":[80,167],"DNN.":[82],"number":[84],"possible":[86],"such":[87],"cross":[88,162,188,213,231],"features":[89,163,172,214,220,232],"combinatorial,":[91],"making":[92],"them":[93],"computationally":[94],"prohibitive":[95],"model.":[97],"Furthermore,":[98],"deployment":[100],"learning":[102],"models":[103,256],"real-world":[105,248],"applications":[106],"has":[107],"also":[108],"highlighted":[109],"need":[111],"interpretability,":[113],"especially":[114],"high-stakes":[116],"applications,":[117],"which":[118],"remains":[119],"another":[120],"issue":[121],"concern":[123],"DNNs.":[125],"In":[126],"this":[127],"paper,":[128],"we":[129,209],"present":[130],"ARM-Net,":[131],"an":[132],"adaptive":[133],"relation":[134],"modeling":[135],"network":[136],"tailored":[137],"lightweight":[143],"framework":[144],"ARMOR":[145],"based":[146],"on":[147,247],"ARM-Net":[148,227,252],"relational":[150],"key":[154],"idea":[155],"model":[158,212,225],"feature":[159],"interactions":[160],"with":[161,218],"selectively":[164],"dynamically,":[166],"first":[168],"transforming":[169],"input":[171,205],"into":[173],"exponential":[174],"space,":[175],"then":[177],"determining":[178],"interaction":[180,183,201],"order":[181],"weights":[184,202],"adaptively":[185],"each":[187,236],"feature.":[189],"We":[190],"propose":[191],"novel":[193],"sparse":[194],"attention":[195],"mechanism":[196],"dynamically":[198],"generate":[199],"given":[203],"tuple,":[206],"so":[207],"explicitly":[211],"arbitrary":[216],"orders":[217],"noisy":[219],"filtered":[221],"selectively.":[222],"Then":[223],"during":[224],"inference,":[226],"specify":[229],"being":[233],"used":[234],"higher":[239],"accuracy":[240],"better":[242],"interpretability.":[243],"Our":[244],"extensive":[245],"experiments":[246],"datasets":[249],"demonstrate":[250],"consistently":[253],"outperforms":[254],"provides":[258],"more":[259],"interpretable":[260],"predictions":[261],"data-driven":[263],"decision":[264],"making.":[265]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2021-07-05T00:00:00"}
