{"id":"https://openalex.org/W3139401600","doi":"https://doi.org/10.1109/bigdata50022.2020.9378447","title":"An Approximation Method for Large Graph Similarity","display_name":"An Approximation Method for Large Graph Similarity","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3139401600","doi":"https://doi.org/10.1109/bigdata50022.2020.9378447","mag":"3139401600"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378447","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378447","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1109/BigData50022.2020.9378447","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100624306","display_name":"Danfeng Zhao","orcid":"https://orcid.org/0000-0003-1936-0826"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danfeng Zhao","raw_affiliation_strings":["Information College, Shanghai Ocean University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information College, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010022619","display_name":"Zhou Huang","orcid":"https://orcid.org/0000-0002-1255-1913"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou Huang","raw_affiliation_strings":["Information College, Shanghai Ocean University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information College, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064086456","display_name":"Feng Zhou","orcid":"https://orcid.org/0000-0002-2906-8127"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhou","raw_affiliation_strings":["School of Computer Science and Technology, Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026941307","display_name":"Antonio Liotta","orcid":"https://orcid.org/0000-0002-2773-4421"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Antonio Liotta","raw_affiliation_strings":["Information College, Shanghai Ocean University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information College, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101780579","display_name":"Dongmei Huang","orcid":"https://orcid.org/0000-0001-6930-2136"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongmei Huang","raw_affiliation_strings":["Information College, Shanghai Ocean University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information College, Shanghai Ocean University, Shanghai, China","institution_ids":["https://openalex.org/I44675526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"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":"4828","last_page":"4835"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9976000189781189,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.5741060972213745},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46735289692878723},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4476437568664551},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3433965742588043},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.30695900321006775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5741060972213745},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46735289692878723},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4476437568664551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3433965742588043},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30695900321006775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378447","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378447","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.39UBZ_INST:11310598830001241","is_oa":true,"landing_page_url":"https://doi.org/10.1109/BigData50022.2020.9378447","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},{"id":"pmh:oai:unibz.it:11310598830001241","is_oa":true,"landing_page_url":"https://bia.unibz.it/esploro/outputs/conferenceProceeding/An-Approximation-Method-for-Large-Graph/991006679798401241","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"}],"best_oa_location":{"id":"pmh:oai:alma.39UBZ_INST:11310598830001241","is_oa":true,"landing_page_url":"https://doi.org/10.1109/BigData50022.2020.9378447","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W74055483","https://openalex.org/W1502619761","https://openalex.org/W1509240356","https://openalex.org/W1965142824","https://openalex.org/W2003863333","https://openalex.org/W2026265169","https://openalex.org/W2056899820","https://openalex.org/W2097827365","https://openalex.org/W2158614393","https://openalex.org/W2170607286","https://openalex.org/W2613296560","https://openalex.org/W2789319383","https://openalex.org/W2899323967","https://openalex.org/W2904520850","https://openalex.org/W2918323453","https://openalex.org/W2924009715","https://openalex.org/W2940927497","https://openalex.org/W2947250710","https://openalex.org/W2955234321","https://openalex.org/W2969585390","https://openalex.org/W2985293587","https://openalex.org/W2996153470","https://openalex.org/W6630171628"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Similarity":[0],"calculation":[1],"of":[2,32,48,64,116,138],"large-scale":[3,49,93],"graphs":[4,50,141],"is":[5,35,72,85,101,122],"essential":[6],"in":[7,128],"big":[8],"data":[9],"classification,":[10],"sorting,":[11],"and":[12,21,29,54,111,131],"other":[13],"work.":[14],"However,":[15],"when":[16],"there":[17],"are":[18,24],"diverse":[19],"attributes":[20,55],"the":[22,27,62,76,89,98,108,114,119,135,139],"vertices":[23],"not":[25],"ordered,":[26],"time":[28],"space":[30],"complexity":[31],"similarity":[33,90,143],"computation":[34],"often":[36],"too":[37],"high.":[38],"This":[39],"paper":[40],"presents":[41],"a":[42,65,80,124],"unified":[43],"representation":[44],"comprehensive":[45,68],"tensor":[46,69],"(CT)":[47],"with":[51],"different":[52],"specifications":[53],"to":[56,74,87,103,126],"save":[57],"space.":[58],"Besides,":[59],"before":[60],"approximation,":[61],"concept":[63],"completely":[66],"satisfied":[67],"(CSCT)":[70],"set":[71],"utilized":[73],"ensure":[75],"attribute":[77],"consistency.":[78],"Then,":[79],"spatial":[81],"mapping":[82],"(SM)":[83],"method":[84],"proposed":[86],"approximate":[88],"between":[91],"two":[92,140],"graphs.":[94],"In":[95],"this":[96],"way,":[97],"computational":[99,120],"memory":[100],"reduced":[102],"O(e+n),":[104],"where":[105],"e":[106],"represents":[107,113],"edge":[109,136],"number,":[110],"n":[112],"number":[115],"vertices.":[117],"Moreover,":[118],"efficiency":[121],"improved":[123],"lot":[125],"O(e1+e2),":[127],"which":[129],"e1":[130],"e2":[132],"respectively":[133],"represent":[134],"numbers":[137],"for":[142],"calculation.":[144]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
