{"id":"https://openalex.org/W4283712247","doi":"https://doi.org/10.48550/arxiv.2206.12733","title":"SiMa: Effective and Efficient Matching Across Data Silos Using Graph Neural Networks","display_name":"SiMa: Effective and Efficient Matching Across Data Silos Using Graph Neural Networks","publication_year":2022,"publication_date":"2022-06-25","ids":{"openalex":"https://openalex.org/W4283712247","doi":"https://doi.org/10.48550/arxiv.2206.12733"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2206.12733","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.12733","pdf_url":"https://arxiv.org/pdf/2206.12733","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.12733","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103144380","display_name":"Christos Koutras","orcid":"https://orcid.org/0000-0003-3015-154X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Koutras, Christos","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046074866","display_name":"Rihan Hai","orcid":"https://orcid.org/0000-0002-3720-6585"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hai, Rihan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073692540","display_name":"Kyriakos Psarakis","orcid":"https://orcid.org/0000-0002-3017-5704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Psarakis, Kyriakos","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019968638","display_name":"Marios Fragkoulis","orcid":"https://orcid.org/0000-0002-0160-0855"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fragkoulis, Marios","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002932353","display_name":"Asterios Katsifodimos","orcid":"https://orcid.org/0000-0002-6717-2945"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katsifodimos, Asterios","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103144380"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"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/T11719","display_name":"Data Quality and Management","score":0.9848999977111816,"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"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9848999977111816,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.977400004863739,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/information-silo","display_name":"Information silo","score":0.8417544364929199},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6633742451667786},{"id":"https://openalex.org/keywords/sima","display_name":"Sima","score":0.6208205223083496},{"id":"https://openalex.org/keywords/column","display_name":"Column (typography)","score":0.5749614238739014},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.573708713054657},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.5567968487739563},{"id":"https://openalex.org/keywords/silo","display_name":"Silo","score":0.46773964166641235},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43936488032341003},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42652034759521484},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4155912399291992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22909867763519287},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16169580817222595},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13126063346862793},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1119498610496521},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10113182663917542},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07909265160560608},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07742452621459961}],"concepts":[{"id":"https://openalex.org/C48255552","wikidata":"https://www.wikidata.org/wiki/Q6031230","display_name":"Information silo","level":3,"score":0.8417544364929199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6633742451667786},{"id":"https://openalex.org/C2777962870","wikidata":"https://www.wikidata.org/wiki/Q2724361","display_name":"Sima","level":2,"score":0.6208205223083496},{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.5749614238739014},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.573708713054657},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.5567968487739563},{"id":"https://openalex.org/C2778024958","wikidata":"https://www.wikidata.org/wiki/Q213643","display_name":"Silo","level":2,"score":0.46773964166641235},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43936488032341003},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42652034759521484},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4155912399291992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22909867763519287},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16169580817222595},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13126063346862793},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1119498610496521},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10113182663917542},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07909265160560608},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07742452621459961},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C8058405","wikidata":"https://www.wikidata.org/wiki/Q46255","display_name":"Geophysics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2206.12733","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.12733","pdf_url":"https://arxiv.org/pdf/2206.12733","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2206.12733","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2206.12733","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.12733","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.12733","pdf_url":"https://arxiv.org/pdf/2206.12733","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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2362191124","https://openalex.org/W2092345840","https://openalex.org/W4236557995","https://openalex.org/W2555139639","https://openalex.org/W2288860943","https://openalex.org/W2199380551","https://openalex.org/W1977446600","https://openalex.org/W2551780525","https://openalex.org/W3176164841","https://openalex.org/W2002685547"],"abstract_inverted_index":{"How":[0],"can":[1],"we":[2,16,39,131],"leverage":[3],"existing":[4,61],"column":[5,62,83,139],"relationships":[6,63,84],"within":[7,64,85],"silos,":[8,49,66],"to":[9,58,78,113],"predict":[10],"similar":[11],"ones":[12],"across":[13,47],"silos?":[14],"Can":[15],"do":[17,25],"this":[18,37],"efficiently":[19],"and":[20,67],"effectively?":[21],"Existing":[22],"matching":[23,45,120],"approaches":[24],"not":[26],"exploit":[27],"prior":[28],"knowledge,":[29],"relying":[30],"on":[31,82],"prohibitively":[32],"expensive":[33],"similarity":[34],"computations.":[35],"In":[36],"paper":[38],"present":[40],"the":[41,91,109,114],"first":[42],"technique":[43],"for":[44],"columns":[46],"data":[48,65],"called":[50],"SiMa,":[51],"which":[52],"leverages":[53],"Graph":[54],"Neural":[55],"Networks":[56],"(GNNs)":[57],"learn":[59],"from":[60],"dataset-specific":[68],"profiles.":[69],"The":[70],"main":[71],"novelty":[72],"of":[73,93,116,125],"SiMa":[74,104,134],"is":[75,105],"its":[76],"ability":[77],"be":[79],"trained":[80],"incrementally":[81],"each":[86],"silo":[87],"individually,":[88],"without":[89],"requiring":[90,123],"consolidation":[92],"all":[94],"datasets":[95],"in":[96],"a":[97],"single":[98],"place.":[99],"Our":[100],"experiments":[101],"show":[102],"that":[103,133],"more":[106],"effective":[107],"than":[108],"-":[110,118],"otherwise":[111],"inapplicable":[112],"setting":[115],"silos":[117],"state-of-the-art":[119,138],"methods,":[121],"while":[122],"orders":[124],"magnitude":[126],"less":[127],"computational":[128],"resources.":[129],"Moreover,":[130],"demonstrate":[132],"considerably":[135],"outperforms":[136],"other":[137],"representation":[140],"learning":[141],"methods.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2022-06-30T00:00:00"}
