{"id":"https://openalex.org/W4386361545","doi":"https://doi.org/10.1109/icccn58024.2023.10230174","title":"An Accurate Graph Generative Model with Tunable Features","display_name":"An Accurate Graph Generative Model with Tunable Features","publication_year":2023,"publication_date":"2023-07-01","ids":{"openalex":"https://openalex.org/W4386361545","doi":"https://doi.org/10.1109/icccn58024.2023.10230174"},"language":"en","primary_location":{"id":"doi:10.1109/icccn58024.2023.10230174","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccn58024.2023.10230174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 32nd International Conference on Computer Communications and Networks (ICCCN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2309.01158","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102287382","display_name":"Takahiro Yokoyama","orcid":null},"institutions":[{"id":"https://openalex.org/I85922643","display_name":"Nagaoka University of Technology","ror":"https://ror.org/00ys1hz88","country_code":"JP","type":"education","lineage":["https://openalex.org/I85922643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Yokoyama","raw_affiliation_strings":["Graduate School of Engineering, Nagaoka University of Technology,Nagaoka,Niigata,Japan","Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Nagaoka University of Technology,Nagaoka,Niigata,Japan","institution_ids":["https://openalex.org/I85922643"]},{"raw_affiliation_string":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan","institution_ids":["https://openalex.org/I85922643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076935419","display_name":"Yoshiki J. Sato","orcid":"https://orcid.org/0000-0002-1750-0373"},"institutions":[{"id":"https://openalex.org/I85922643","display_name":"Nagaoka University of Technology","ror":"https://ror.org/00ys1hz88","country_code":"JP","type":"education","lineage":["https://openalex.org/I85922643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiki Sato","raw_affiliation_strings":["Graduate School of Engineering, Nagaoka University of Technology,Nagaoka,Niigata,Japan","Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Nagaoka University of Technology,Nagaoka,Niigata,Japan","institution_ids":["https://openalex.org/I85922643"]},{"raw_affiliation_string":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan","institution_ids":["https://openalex.org/I85922643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019172487","display_name":"Sho Tsugawa","orcid":"https://orcid.org/0000-0001-7837-2857"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sho Tsugawa","raw_affiliation_strings":["Information and Systems, University of Tsukuba,Faculity of Engineering,Tsukuba,Ibaraki,Japan","Faculity of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information and Systems, University of Tsukuba,Faculity of Engineering,Tsukuba,Ibaraki,Japan","institution_ids":["https://openalex.org/I146399215"]},{"raw_affiliation_string":"Faculity of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020753132","display_name":"Kohei Watabe","orcid":"https://orcid.org/0000-0002-9246-9740"},"institutions":[{"id":"https://openalex.org/I85922643","display_name":"Nagaoka University of Technology","ror":"https://ror.org/00ys1hz88","country_code":"JP","type":"education","lineage":["https://openalex.org/I85922643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kohei Watabe","raw_affiliation_strings":["Graduate School of Engineering, Nagaoka University of Technology,Nagaoka,Niigata,Japan","Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Nagaoka University of Technology,Nagaoka,Niigata,Japan","institution_ids":["https://openalex.org/I85922643"]},{"raw_affiliation_string":"Graduate School of Engineering, Nagaoka University of Technology, Nagaoka, Niigata, Japan","institution_ids":["https://openalex.org/I85922643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1553,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44860861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9990000128746033,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9975000023841858,"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":0.9947999715805054,"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/computer-science","display_name":"Computer science","score":0.7016389966011047},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5472800135612488},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5415383577346802},{"id":"https://openalex.org/keywords/topological-graph-theory","display_name":"Topological graph theory","score":0.5026886463165283},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4981117248535156},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.49732664227485657},{"id":"https://openalex.org/keywords/graph-product","display_name":"Graph product","score":0.41710221767425537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2995854616165161},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.24571654200553894},{"id":"https://openalex.org/keywords/pathwidth","display_name":"Pathwidth","score":0.1945032775402069}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7016389966011047},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5472800135612488},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5415383577346802},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.5026886463165283},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4981117248535156},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.49732664227485657},{"id":"https://openalex.org/C68103157","wikidata":"https://www.wikidata.org/wiki/Q569347","display_name":"Graph product","level":5,"score":0.41710221767425537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2995854616165161},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.24571654200553894},{"id":"https://openalex.org/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.1945032775402069}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icccn58024.2023.10230174","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccn58024.2023.10230174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 32nd International Conference on Computer Communications and Networks (ICCCN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2309.01158","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.01158","pdf_url":"https://arxiv.org/pdf/2309.01158","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":"pmh:oai:arXiv.org:2309.01158","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.01158","pdf_url":"https://arxiv.org/pdf/2309.01158","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386361545.pdf"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2046522752","https://openalex.org/W3098040575","https://openalex.org/W4321021049"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W4238433571","https://openalex.org/W2967848559","https://openalex.org/W4299831724","https://openalex.org/W4283803360"],"abstract_inverted_index":{"A":[0],"graph":[1,53,80,94,101,135,151],"is":[2],"a":[3,71,92,117,127,149],"very":[4],"common":[5],"and":[6,14,33,140,145],"powerful":[7],"data":[8],"structure":[9],"used":[10],"for":[11,42,46,74,109],"modeling":[12],"communication":[13],"social":[15],"networks.":[16],"Models":[17],"that":[18,76,154],"generate":[19],"graphs":[20,43,48,75,84,139,160],"with":[21,56,165],"arbitrary":[22],"features":[23,58,81,90,102,136,156],"are":[24,44,161],"important":[25],"basic":[26],"technologies":[27],"in":[28,63,103,157],"repeated":[29],"simulations":[30],"of":[31,35,82,88,91,100,123,134,137],"networks":[32],"prediction":[34],"topology":[36],"changes.":[37],"Although":[38],"existing":[39],"generative":[40,72],"models":[41,55],"useful":[45],"providing":[47],"similar":[49],"to":[50,119,130],"real-world":[51,150],"graphs,":[52],"generation":[54],"tunable":[57],"have":[59,68],"been":[60,107],"less":[61],"explored":[62],"the":[64,89,97,121,155,158],"field.":[65],"Previously,":[66],"we":[67,115],"proposed":[69],"GraphTune,":[70],"model":[73],"continuously":[77],"tune":[78],"specific":[79],"generated":[83,138,159],"while":[85],"maintaining":[86],"most":[87],"given":[93],"dataset.":[95],"However,":[96],"tuning":[98],"accuracy":[99,122],"GraphTune":[104,124],"has":[105],"not":[106],"sufficient":[108],"practical":[110],"applications.":[111],"In":[112],"this":[113],"paper,":[114],"propose":[116],"method":[118],"improve":[120],"by":[125,141],"adding":[126],"new":[128],"mechanism":[129],"feed":[131],"back":[132],"errors":[133],"training":[142],"them":[143],"alternately":[144],"independently.":[146],"Experiments":[147],"on":[148],"dataset":[152],"showed":[153],"accurately":[162],"tuned":[163],"compared":[164],"conventional":[166],"models.":[167]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}