{"id":"https://openalex.org/W3108686274","doi":"https://doi.org/10.1093/jcde/qwaa075","title":"A geometric deep learning approach for checking element-to-entity mappings in infrastructure building information models","display_name":"A geometric deep learning approach for checking element-to-entity mappings in infrastructure building information models","publication_year":2020,"publication_date":"2020-10-28","ids":{"openalex":"https://openalex.org/W3108686274","doi":"https://doi.org/10.1093/jcde/qwaa075","mag":"3108686274"},"language":"en","primary_location":{"id":"doi:10.1093/jcde/qwaa075","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jcde/qwaa075","pdf_url":"https://academic.oup.com/jcde/article-pdf/8/1/239/36097792/qwaa075.pdf","source":{"id":"https://openalex.org/S2485147958","display_name":"Journal of Computational Design and Engineering","issn_l":"2288-4300","issn":["2288-4300","2288-5048"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Design and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://academic.oup.com/jcde/article-pdf/8/1/239/36097792/qwaa075.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102533112","display_name":"Bonsang Koo","orcid":"https://orcid.org/0000-0002-1029-3375"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bonsang Koo","raw_affiliation_strings":["Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036782765","display_name":"Rae-Kyu Jung","orcid":"https://orcid.org/0000-0002-5042-9177"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Raekyu Jung","raw_affiliation_strings":["Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-5042-9177","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059399393","display_name":"Youngsu Yu","orcid":"https://orcid.org/0000-0003-3593-0657"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Youngsu Yu","raw_affiliation_strings":["Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014921173","display_name":"Inhan Kim","orcid":"https://orcid.org/0000-0002-1426-108X"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Inhan Kim","raw_affiliation_strings":["Department of Architecture, Kyung Hee University, Gyeonggi, 17104, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Architecture, Kyung Hee University, Gyeonggi, 17104, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059399393"],"corresponding_institution_ids":["https://openalex.org/I118373667"],"apc_list":{"value":1650,"currency":"USD","value_usd":1650},"apc_paid":{"value":1650,"currency":"USD","value_usd":1650},"fwci":8.059,"has_fulltext":true,"cited_by_count":45,"citation_normalized_percentile":{"value":0.9714359,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"8","issue":"1","first_page":"239","last_page":"250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11006","display_name":"BIM and Construction Integration","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/building-information-modeling","display_name":"Building information modeling","score":0.7773855924606323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6858574151992798},{"id":"https://openalex.org/keywords/information-model","display_name":"Information model","score":0.6194582581520081},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.559038519859314},{"id":"https://openalex.org/keywords/interoperability","display_name":"Interoperability","score":0.4981663227081299},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4660758972167969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45600685477256775},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.420159250497818},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40265175700187683},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.29401934146881104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2693674564361572},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22873002290725708}],"concepts":[{"id":"https://openalex.org/C66862320","wikidata":"https://www.wikidata.org/wiki/Q842017","display_name":"Building information modeling","level":3,"score":0.7773855924606323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6858574151992798},{"id":"https://openalex.org/C21338462","wikidata":"https://www.wikidata.org/wiki/Q1662581","display_name":"Information model","level":2,"score":0.6194582581520081},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.559038519859314},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.4981663227081299},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4660758972167969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45600685477256775},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.420159250497818},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40265175700187683},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.29401934146881104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2693674564361572},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22873002290725708},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2778648169","wikidata":"https://www.wikidata.org/wiki/Q967768","display_name":"Compatibility (geochemistry)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/jcde/qwaa075","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jcde/qwaa075","pdf_url":"https://academic.oup.com/jcde/article-pdf/8/1/239/36097792/qwaa075.pdf","source":{"id":"https://openalex.org/S2485147958","display_name":"Journal of Computational Design and Engineering","issn_l":"2288-4300","issn":["2288-4300","2288-5048"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Design and Engineering","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1093/jcde/qwaa075","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jcde/qwaa075","pdf_url":"https://academic.oup.com/jcde/article-pdf/8/1/239/36097792/qwaa075.pdf","source":{"id":"https://openalex.org/S2485147958","display_name":"Journal of Computational Design and Engineering","issn_l":"2288-4300","issn":["2288-4300","2288-5048"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Design and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321292","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542"},{"id":"https://openalex.org/F4320321294","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07"},{"id":"https://openalex.org/F4320327756","display_name":"National University of Science and Technology","ror":"https://ror.org/019vsm959"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3108686274.pdf","grobid_xml":"https://content.openalex.org/works/W3108686274.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W46659105","https://openalex.org/W335247780","https://openalex.org/W1532934333","https://openalex.org/W1583948418","https://openalex.org/W1968200193","https://openalex.org/W1991959674","https://openalex.org/W1999014394","https://openalex.org/W2021526019","https://openalex.org/W2060593689","https://openalex.org/W2066023832","https://openalex.org/W2129918481","https://openalex.org/W2211722331","https://openalex.org/W2218653053","https://openalex.org/W2253149825","https://openalex.org/W2346107092","https://openalex.org/W2401589188","https://openalex.org/W2521426873","https://openalex.org/W2558748708","https://openalex.org/W2582736118","https://openalex.org/W2593374237","https://openalex.org/W2741956695","https://openalex.org/W2747776519","https://openalex.org/W2789756826","https://openalex.org/W2793768763","https://openalex.org/W2795863156","https://openalex.org/W2804172331","https://openalex.org/W2807933854","https://openalex.org/W2886183793","https://openalex.org/W2888240501","https://openalex.org/W2902341708","https://openalex.org/W2903041390","https://openalex.org/W2957927655","https://openalex.org/W3045201668","https://openalex.org/W3081663048","https://openalex.org/W3104030692","https://openalex.org/W3105918501","https://openalex.org/W3122730524","https://openalex.org/W4236965008","https://openalex.org/W4285719527","https://openalex.org/W4301409532","https://openalex.org/W6602002561","https://openalex.org/W6611542402","https://openalex.org/W6631803645","https://openalex.org/W6637108133","https://openalex.org/W6640300118","https://openalex.org/W6648737282","https://openalex.org/W6691469954","https://openalex.org/W6730760897","https://openalex.org/W6739778489","https://openalex.org/W6746471504","https://openalex.org/W6763422710","https://openalex.org/W6764445119","https://openalex.org/W6780777202","https://openalex.org/W6782442249","https://openalex.org/W7017884376","https://openalex.org/W7033919612"],"related_works":["https://openalex.org/W1581272063","https://openalex.org/W2343576784","https://openalex.org/W2985529868","https://openalex.org/W2132976026","https://openalex.org/W4367678427","https://openalex.org/W4383818408","https://openalex.org/W430283928","https://openalex.org/W2891560538","https://openalex.org/W3132906903","https://openalex.org/W4385737655"],"abstract_inverted_index":{"Abstract":[0],"Data":[1],"interoperability":[2],"between":[3,63],"domain-specific":[4],"applications":[5],"is":[6,51,86],"a":[7,20,148,191],"key":[8],"prerequisite":[9],"for":[10,23],"building":[11],"information":[12,26],"modeling":[13],"(BIM)":[14],"to":[15,44,54,72,102,135,186,196,207],"solidify":[16],"its":[17],"position":[18],"as":[19,157,214],"central":[21],"medium":[22],"collaboration":[24],"and":[25,40,57,66,89,129,133,163,169,178,203],"sharing":[27],"in":[28,48,61,144,200],"the":[29,76,81,95,108,113,158,188,209,212],"construction":[30],"industry.":[31],"The":[32],"Industry":[33],"Foundation":[34],"Classes":[35],"(IFC)":[36],"provides":[37],"an":[38],"open":[39],"neutral":[41],"data":[42,46,55],"format":[43],"standardize":[45],"exchanges":[47],"BIM,":[49],"but":[50],"often":[52],"exposed":[53],"loss":[56],"misclassifications.":[58],"Concretely,":[59],"errors":[60],"mappings":[62],"BIM":[64,105,142],"elements":[65,143],"IFC":[67,82],"entities":[68],"may":[69],"occur":[70],"due":[71],"manual":[73],"omissions":[74],"or":[75],"lack":[77],"of":[78,80,97,111,115,139,150,167,176,190,211],"awareness":[79],"schema":[83],"itself,":[84],"which":[85,182],"broadly":[87],"defined":[88],"highly":[90],"complex.":[91],"This":[92],"study":[93],"explored":[94],"use":[96],"geometric":[98],"deep":[99],"learning":[100],"models":[101,119],"classify":[103,136],"infrastructure":[104],"elements,":[106],"with":[107,120,161,172],"ultimate":[109],"goal":[110],"automating":[112],"prechecking":[114],"BIM-to-IFC":[116],"mappings.":[117],"Two":[118],"proven":[121],"classification":[122],"performance,":[123],"Multi-View":[124],"Convolutional":[125],"Neural":[126],"Network":[127],"(MVCNN)":[128],"PointNet,":[130],"were":[131],"trained":[132],"tested":[134],"10":[137],"types":[138],"commonly":[140],"used":[141],"road":[145],"infrastructure,":[146],"using":[147],"dataset":[149],"1496":[151],"3D":[152,192],"models.":[153],"Results":[154],"revealed":[155],"MVCNN":[156],"superior":[159],"model":[160],"ACC":[162],"F1":[164],"score":[165],"values":[166,175],"0.98":[168],"0.98,":[170],"compared":[171],"PointNet's":[173],"corresponding":[174],"0.83":[177],"0.87,":[179],"respectively.":[180],"MVCNN,":[181],"employs":[183],"multiple":[184],"images":[185],"learn":[187],"features":[189],"artifact,":[193],"was":[194],"able":[195],"discern":[197],"subtle":[198],"differences":[199],"their":[201],"shapes":[202],"geometry.":[204],"PointNet":[205],"seems":[206],"lose":[208],"granularity":[210],"shapes,":[213],"it":[215],"uses":[216],"points":[217],"partially":[218],"selected":[219],"from":[220],"point":[221],"clouds.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}