{"id":"https://openalex.org/W4416249436","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227325","title":"Spectral Core Entropy Based Graph Data Generation Algorithm","display_name":"Spectral Core Entropy Based Graph Data Generation Algorithm","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416249436","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227325"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5107079497","display_name":"Dongdong Nian","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongdong Nian","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111345721","display_name":"Dayu Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dayu Qin","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038228706","display_name":"Er\u00e7an E. Kuruo\u011flu","orcid":"https://orcid.org/0000-0002-2608-8034"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ercan Engin Kuruoglu","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5107079497"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36730958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.8830999732017517,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.8830999732017517,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11476","display_name":"Graph theory and applications","score":0.04280000180006027,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.026599999517202377,"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/entropy","display_name":"Entropy (arrow of time)","score":0.5001999735832214},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49459999799728394},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.486299991607666},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.44119998812675476},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.4198000133037567},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.34700000286102295},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.3287999927997589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5167999863624573},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.486299991607666},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45649999380111694},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.44119998812675476},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42969998717308044},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3237999975681305},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2842000126838684},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C2985906921","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Spectral properties","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1986671133","https://openalex.org/W2023313300","https://openalex.org/W2041390652","https://openalex.org/W2054439077","https://openalex.org/W2080635178","https://openalex.org/W2096939574","https://openalex.org/W2114704115","https://openalex.org/W2124637492","https://openalex.org/W2206840988","https://openalex.org/W2894843783","https://openalex.org/W4221138852","https://openalex.org/W4289436753","https://openalex.org/W4385732423"],"related_works":[],"abstract_inverted_index":{"Molecule":[0],"graph":[1,29,67,151],"generation":[2,152],"plays":[3],"a":[4,62,90,94,132],"crucial":[5],"role":[6],"in":[7,54,126],"the":[8,18,42,70,75,84,99,142],"field":[9],"of":[10,22,89,101,136,144],"drug":[11,24,55,137,156],"discovery,":[12],"as":[13,93],"it":[14],"can":[15],"significantly":[16],"expedite":[17],"identification":[19],"and":[20,48,86,114,128],"development":[21],"potential":[23,143],"candidates.":[25,138],"Although":[26],"many":[27],"deep":[28],"generative":[30,76],"models":[31],"have":[32],"been":[33],"developed,":[34],"they":[35],"often":[36],"generate":[37],"molecular":[38,103,116,150],"graphs":[39],"without":[40],"optimizing":[41],"samples,":[43],"leading":[44,130],"to":[45,97,131],"limited":[46],"validity":[47,127],"uniqueness,":[49,129],"which":[50,82],"are":[51],"key":[52],"factors":[53],"discovery.":[56,157],"In":[57],"this":[58],"work,":[59],"we":[60],"introduce":[61],"novel":[63],"approach":[64],"that":[65],"incorporates":[66],"statistics,":[68],"specifically":[69],"Spectral":[71,79,146],"Core":[72,80,147],"Entropy,":[73,81],"into":[74,149],"process.":[77],"The":[78],"measures":[83],"complexity":[85],"structural":[87],"diversity":[88],"graph,":[91],"serves":[92],"guiding":[95],"metric":[96],"enhance":[98],"quality":[100],"generated":[102],"graphs.":[104],"By":[105],"incorporating":[106],"entropy-based":[107],"measures,":[108],"our":[109],"method":[110],"generates":[111],"more":[112,133],"valid":[113],"unique":[115],"structures":[117],"than":[118],"baseline":[119],"models.":[120],"Empirical":[121],"evaluations":[122],"show":[123],"significant":[124],"improvements":[125],"diverse":[134],"set":[135],"These":[139],"results":[140],"highlight":[141],"integrating":[145],"Entropy":[148],"for":[153],"advancing":[154],"computational":[155]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}