{"id":"https://openalex.org/W4320084159","doi":"https://doi.org/10.1007/978-3-031-21534-6_2","title":"Generating Synthetic Graph Data from Random Network Models","display_name":"Generating Synthetic Graph Data from Random Network Models","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4320084159","doi":"https://doi.org/10.1007/978-3-031-21534-6_2"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-21534-6_2","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"book-chapter","type_crossref":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/978-3-031-21534-6_2","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103183708","display_name":"Ulrich Meyer","orcid":"https://orcid.org/0000-0002-1197-3153"},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"funder","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ulrich Meyer","raw_affiliation_strings":["Goethe University Frankfurt, Frankfurt, Germany"],"affiliations":[{"raw_affiliation_string":"Goethe University Frankfurt, Frankfurt, Germany","institution_ids":["https://openalex.org/I114090438"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052142376","display_name":"Manuel Penschuck","orcid":"https://orcid.org/0000-0003-2630-7548"},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"funder","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Manuel Penschuck","raw_affiliation_strings":["Goethe University Frankfurt, Frankfurt, Germany"],"affiliations":[{"raw_affiliation_string":"Goethe University Frankfurt, Frankfurt, Germany","institution_ids":["https://openalex.org/I114090438"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":59},"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"38"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":1.0,"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":1.0,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.999,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.995,"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":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.83043456},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5833336},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.56565213},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.45513},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33417875},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33104688}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-21534-6_2","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-21534-6_2","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":42,"referenced_works":["https://openalex.org/W1482680420","https://openalex.org/W1646238826","https://openalex.org/W1756477312","https://openalex.org/W1888264395","https://openalex.org/W1981561414","https://openalex.org/W1987794091","https://openalex.org/W1988398836","https://openalex.org/W1991408655","https://openalex.org/W2008006577","https://openalex.org/W2008620264","https://openalex.org/W2018480107","https://openalex.org/W2038142281","https://openalex.org/W2080450835","https://openalex.org/W2088209891","https://openalex.org/W2095293504","https://openalex.org/W2289974125","https://openalex.org/W2293947850","https://openalex.org/W2401915092","https://openalex.org/W2607372450","https://openalex.org/W2750600085","https://openalex.org/W2754662780","https://openalex.org/W2886935179","https://openalex.org/W2945703238","https://openalex.org/W2963017687","https://openalex.org/W2963166370","https://openalex.org/W2963653837","https://openalex.org/W2963760219","https://openalex.org/W2963979722","https://openalex.org/W2963982460","https://openalex.org/W2963987802","https://openalex.org/W2964251804","https://openalex.org/W2964263237","https://openalex.org/W2971375767","https://openalex.org/W2978499064","https://openalex.org/W3021587765","https://openalex.org/W3041685368","https://openalex.org/W3099643767","https://openalex.org/W3101631150","https://openalex.org/W3122247640","https://openalex.org/W390146837","https://openalex.org/W4238452917","https://openalex.org/W4252973173"],"related_works":["https://openalex.org/W4300257700","https://openalex.org/W4250665764","https://openalex.org/W4248914732","https://openalex.org/W4242560956","https://openalex.org/W3130470475","https://openalex.org/W2782271697","https://openalex.org/W2541851899","https://openalex.org/W2497425261","https://openalex.org/W2170524605","https://openalex.org/W1624705498"],"abstract_inverted_index":{"Abstract":[0],"Network":[1],"models":[2,61,120],"are":[3],"developed":[4],"and":[5,15,65,103,123],"used":[6],"in":[7],"various":[8,118],"fields":[9],"of":[10,21,37,47,97],"science":[11],"as":[12],"their":[13],"design":[14],"analysis":[16],"can":[17,27,43,67],"improve":[18],"the":[19,22,45,54,88,95,134],"understanding":[20],"numerous":[23,86],"complex":[24],"systems":[25],"we":[26,132],"observe":[28],"on":[29,147],"an":[30,34],"everyday":[31],"basis.":[32],"From":[33],"algorithmics":[35],"point":[36],"view,":[38],"structural":[39],"insights":[40],"into":[41],"networks":[42],"guide":[44],"engineering":[46],"tailor-made":[48],"graph":[49,63,112,119,140],"algorithms":[50,116],"required":[51],"to":[52,101,125],"face":[53],"big":[55],"data":[56],"challenge.":[57],"By":[58],"design,":[59],"network":[60,83],"describe":[62],"classes":[64],"therefore":[66],"often":[68],"provide":[69],"meaningful":[70],"synthetic":[71],"instances":[72,90],"whose":[73],"applications":[74],"include":[75],"experimental":[76,127],"case":[77],"studies.":[78],"While":[79],"there":[80],"exist":[81],"public":[82],"libraries":[84],"with":[85],"datasets,":[87],"available":[89],"do":[91],"not":[92],"fully":[93],"satisfy":[94],"needs":[96],"experimenters,":[98],"especially":[99],"pertaining":[100],"size":[102],"diversity.":[104],"As":[105],"several":[106],"SPP":[107],"1736":[108],"projects":[109],"engineered":[110],"practical":[111],"algorithms,":[113],"multiple":[114],"sampling":[115],"for":[117,137],"were":[121],"designed":[122],"implemented":[124],"supplement":[126],"campaigns.":[128],"In":[129],"this":[130],"chapter,":[131],"survey":[133],"results":[135],"obtained":[136],"these":[138],"so-called":[139],"generators.":[141],"This":[142],"chapter":[143],"is":[144],"partially":[145],"based":[146],"[43":[148],"SPP].":[149]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4320084159","counts_by_year":[],"updated_date":"2025-03-28T04:42:13.596568","created_date":"2023-02-12"}