{"id":"https://openalex.org/W4362453183","doi":"https://doi.org/10.1145/3589643","title":"Graph Neural Networks with Motisf-aware for Tenuous Subgraph Finding","display_name":"Graph Neural Networks with Motisf-aware for Tenuous Subgraph Finding","publication_year":2023,"publication_date":"2023-04-01","ids":{"openalex":"https://openalex.org/W4362453183","doi":"https://doi.org/10.1145/3589643"},"language":"en","primary_location":{"id":"doi:10.1145/3589643","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589643","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100705864","display_name":"Heli Sun","orcid":"https://orcid.org/0000-0003-0818-0301"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Heli Sun","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101907365","display_name":"Miaomiao Sun","orcid":"https://orcid.org/0009-0002-1427-2472"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miaomiao Sun","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101497266","display_name":"Liu Xue-chun","orcid":"https://orcid.org/0000-0001-5616-5822"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuechun Liu","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380600","display_name":"Linlin Zhu","orcid":"https://orcid.org/0000-0001-7312-6534"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Zhu","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101469086","display_name":"Liang He","orcid":"https://orcid.org/0000-0002-6463-5158"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang He","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100684400","display_name":"Xiaolin Jia","orcid":"https://orcid.org/0009-0005-6641-7807"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Jia","raw_affiliation_strings":["Xi\u2019an Jiaotong University, Xi\u2019an, China","Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101435511","display_name":"Yuan Chen","orcid":"https://orcid.org/0009-0009-2321-4910"},"institutions":[{"id":"https://openalex.org/I4210120069","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25","country_code":"CN","type":"funder","lineage":["https://openalex.org/I4210120069","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Chen","raw_affiliation_strings":["Information Center of Ministry of Science and Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Information Center of Ministry of Science and Technology, Beijing, China","institution_ids":["https://openalex.org/I4210120069"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100705864"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.6993,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7413891,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"17","issue":"8","first_page":"1","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5568206310272217},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.5567323565483093},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.49851536750793457},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.49581584334373474},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49407079815864563},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40869638323783875},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33982208371162415},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.11392471194267273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5568206310272217},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.5567323565483093},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.49851536750793457},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.49581584334373474},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49407079815864563},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40869638323783875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33982208371162415},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.11392471194267273},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3589643","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3589643","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1352558047","display_name":null,"funder_award_id":"2020KW-002","funder_id":"https://openalex.org/F4320336350","funder_display_name":"Key Research and Development Projects of Shaanxi Province"},{"id":"https://openalex.org/G8138465539","display_name":null,"funder_award_id":"62072365 and 61772392","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336350","display_name":"Key Research and Development Projects of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W49573773","https://openalex.org/W1512140523","https://openalex.org/W1888005072","https://openalex.org/W2036836182","https://openalex.org/W2046383614","https://openalex.org/W2090891622","https://openalex.org/W2124536061","https://openalex.org/W2125895010","https://openalex.org/W2139694940","https://openalex.org/W2153624566","https://openalex.org/W2154851992","https://openalex.org/W2241571695","https://openalex.org/W2393319904","https://openalex.org/W2415243320","https://openalex.org/W2470861207","https://openalex.org/W2543598748","https://openalex.org/W2593237279","https://openalex.org/W2604379690","https://openalex.org/W2743418339","https://openalex.org/W2768859421","https://openalex.org/W2809323004","https://openalex.org/W2809418595","https://openalex.org/W2889468426","https://openalex.org/W2890158617","https://openalex.org/W2907492528","https://openalex.org/W2914034291","https://openalex.org/W2962756421","https://openalex.org/W2963224980","https://openalex.org/W2963823727","https://openalex.org/W2983864285","https://openalex.org/W3026423472","https://openalex.org/W3080834109","https://openalex.org/W3082144291","https://openalex.org/W3104097132","https://openalex.org/W4297733535"],"related_works":["https://openalex.org/W2532922352","https://openalex.org/W231720905","https://openalex.org/W2604893261","https://openalex.org/W1482551403","https://openalex.org/W2361654510","https://openalex.org/W2128390795","https://openalex.org/W2954463587","https://openalex.org/W2604114816","https://openalex.org/W2393701947","https://openalex.org/W2915540008"],"abstract_inverted_index":{"Tenuous":[0],"subgraph":[1,7,81,132,192],"finding":[2,82],"aims":[3],"to":[4,44,102,128,161],"detect":[5],"a":[6,70,84,99,106,117,130,138,156,166,169],"with":[8,77],"few":[9],"social":[10],"interactions":[11],"and":[12,42,177,191],"weak":[13],"relationships":[14],"among":[15],"nodes.":[16,96],"Despite":[17],"significant":[18],"efforts":[19],"made":[20],"on":[21,37,116,174],"this":[22,66],"task,":[23],"they":[24,57],"are":[25],"mostly":[26],"carried":[27],"out":[28],"in":[29,125,189],"view":[30],"of":[31,62,165],"graph-structured":[32],"data.":[33],"These":[34],"methods":[35],"depend":[36],"calculating":[38],"the":[39,47,53,60,92,110,149,163,175],"shortest":[40],"path":[41],"need":[43],"enumerate":[45],"all":[46,58],"paths":[48],"between":[49,95,152],"nodes,":[50,153],"which":[51],"suffer":[52],"combinatorial":[54],"explosion.":[55],"Moreover,":[56],"lack":[59],"integration":[61],"neighborhood":[63,85],"information.":[64],"To":[65],"end,":[67],"we":[68,121,154],"propose":[69],"novel":[71,157],"model":[72],"named":[73],"Graph":[74],"Neural":[75],"Network":[76],"Motif-aware":[78],"for":[79],"tenuous":[80,131],"(GNNM),":[83],"aggregation-based":[86],"GNN":[87,100],"framework":[88],"that":[89,143,181],"can":[90],"capture":[91,148],"latent":[93,150],"relationship":[94],"We":[97],"design":[98,122],"module":[101],"project":[103],"nodes":[104,114],"into":[105],"low-dimensional":[107],"vector":[108,126],"combining":[109],"higher-order":[111],"correlation":[112],"within":[113],"based":[115],"motif-aware":[118],"module.":[119],"Then":[120],"greedy":[123],"algorithms":[124,188],"space":[127],"obtain":[129],"whose":[133],"size":[134],"is":[135],"greater":[136],"than":[137],"specified":[139],"constraint.":[140],"Particularly,":[141],"considering":[142],"existing":[144,187],"evaluation":[145],"indicators":[146],"cannot":[147],"friendship":[151],"introduce":[155],"Potential":[158],"Friend":[159],"concept":[160],"measure":[162],"tenuity":[164],"graph":[167],"from":[168],"new":[170],"perspective.":[171],"Experimental":[172],"results":[173],"real-world":[176],"synthetic":[178],"datasets":[179],"demonstrate":[180],"our":[182],"proposed":[183],"method":[184],"GNNM":[185],"outperforms":[186],"efficiency":[190],"quality.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
