{"id":"https://openalex.org/W2952066860","doi":"https://doi.org/10.1186/s40537-019-0218-z","title":"STVG: an evolutionary graph framework for analyzing fast-evolving networks","display_name":"STVG: an evolutionary graph framework for analyzing fast-evolving networks","publication_year":2019,"publication_date":"2019-06-21","ids":{"openalex":"https://openalex.org/W2952066860","doi":"https://doi.org/10.1186/s40537-019-0218-z","mag":"2952066860"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-019-0218-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-019-0218-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-019-0218-z","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-019-0218-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078675329","display_name":"Iyke Maduako","orcid":"https://orcid.org/0000-0002-7260-3666"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ikechukwu Maduako","raw_affiliation_strings":["People in Motion Lab, University of New Brunswick, 15 Dineen Drive, Fredericton, NB, E3B 5A3, Canada"],"raw_orcid":"https://orcid.org/0000-0002-7260-3666","affiliations":[{"raw_affiliation_string":"People in Motion Lab, University of New Brunswick, 15 Dineen Drive, Fredericton, NB, E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068240080","display_name":"M\u00f3nica Wachowicz","orcid":"https://orcid.org/0000-0002-4659-0101"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Monica Wachowicz","raw_affiliation_strings":["People in Motion Lab, University of New Brunswick, 15 Dineen Drive, Fredericton, NB, E3B 5A3, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"People in Motion Lab, University of New Brunswick, 15 Dineen Drive, Fredericton, NB, E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070206194","display_name":"Trevor Hanson","orcid":"https://orcid.org/0000-0002-8505-7262"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Trevor Hanson","raw_affiliation_strings":["Civil Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB, E3B 5A3, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Civil Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB, E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5078675329"],"corresponding_institution_ids":["https://openalex.org/I106938459"],"apc_list":{"value":1990,"currency":"USD","value_usd":1990},"apc_paid":{"value":1990,"currency":"USD","value_usd":1990},"fwci":2.7347,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89326969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9980000257492065,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7615057229995728},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5205655694007874},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4938808083534241},{"id":"https://openalex.org/keywords/snapshot","display_name":"Snapshot (computer storage)","score":0.49350202083587646},{"id":"https://openalex.org/keywords/graph-database","display_name":"Graph database","score":0.4111584424972534},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10276633501052856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7615057229995728},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5205655694007874},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4938808083534241},{"id":"https://openalex.org/C55282118","wikidata":"https://www.wikidata.org/wiki/Q252683","display_name":"Snapshot (computer storage)","level":2,"score":0.49350202083587646},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.4111584424972534},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10276633501052856}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-019-0218-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-019-0218-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-019-0218-z","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b42922f7f3c24fd2b4538f5ba19ec9e2","is_oa":true,"landing_page_url":"https://doaj.org/article/b42922f7f3c24fd2b4538f5ba19ec9e2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 6, Iss 1, Pp 1-24 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-019-0218-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-019-0218-z","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-019-0218-z","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307791","display_name":"Cisco Systems","ror":"https://ror.org/03yt1ez60"},{"id":"https://openalex.org/F4320325463","display_name":"Tertiary Education Trust Fund","ror":null},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2952066860.pdf","grobid_xml":"https://content.openalex.org/works/W2952066860.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W177842927","https://openalex.org/W1484936125","https://openalex.org/W1540538690","https://openalex.org/W1912056476","https://openalex.org/W1981136949","https://openalex.org/W1982459859","https://openalex.org/W1982469530","https://openalex.org/W1996557842","https://openalex.org/W2027374262","https://openalex.org/W2035057445","https://openalex.org/W2046598510","https://openalex.org/W2053128542","https://openalex.org/W2111350126","https://openalex.org/W2112056172","https://openalex.org/W2119075126","https://openalex.org/W2122710250","https://openalex.org/W2126064871","https://openalex.org/W2131681506","https://openalex.org/W2153336132","https://openalex.org/W2154875162","https://openalex.org/W2168899621","https://openalex.org/W2242505269","https://openalex.org/W2290003527","https://openalex.org/W2292851029","https://openalex.org/W2516141140","https://openalex.org/W2517102695","https://openalex.org/W2585072743","https://openalex.org/W2736072005","https://openalex.org/W2748079855","https://openalex.org/W2889189281","https://openalex.org/W2890659396","https://openalex.org/W2904516392","https://openalex.org/W2962763119","https://openalex.org/W2963681731","https://openalex.org/W3098864638","https://openalex.org/W3101819207","https://openalex.org/W6677782763","https://openalex.org/W6856110994"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2542847180","https://openalex.org/W3034994054","https://openalex.org/W2296161130","https://openalex.org/W2395448265","https://openalex.org/W3115442681","https://openalex.org/W2007838763","https://openalex.org/W4386112722","https://openalex.org/W2391000461","https://openalex.org/W2972311463"],"abstract_inverted_index":{"Sequence":[0],"of":[1,42,44,71,75,105,112,120],"graph":[2,47,77,93,107,114,138,186,191,214],"snapshots":[3],"have":[4],"been":[5],"commonly":[6],"utilized":[7],"in":[8,13,36,116,135,182,203],"literature":[9],"to":[10,51,101,130,151,176,218],"represent":[11],"changes":[12,119],"a":[14,59,87,106],"dynamic":[15],"graph.":[16],"This":[17,57],"approach":[18,100,129],"may":[19],"be":[20,174],"suitable":[21],"for":[22],"small-size":[23],"and":[24,38,142,158,178,194,224],"slowly":[25],"evolving":[26],"graphs;":[27],"however,":[28],"it":[29],"is":[30],"associated":[31],"with":[32,216],"high":[33,132],"storage":[34,133],"overhead":[35,134],"massive":[37],"fast-evolving":[39],"graphs":[40,154],"because":[41],"replication":[43],"the":[45,68,73,76,98,103,110,113,117,149,169,204],"entire":[46],"from":[48],"one":[49],"snapshot":[50],"another":[52],"at":[53,155,221],"shorter":[54],"temporal":[55,80,164,226],"resolutions.":[56,81,165,227],"presents":[58],"drawback":[60],"especially":[61],"where":[62,139],"efficient":[63],"evolutionary":[64,180,201],"analytics":[65],"relies":[66],"on":[67,90],"explanatory":[69],"power":[70],"representing":[72],"dynamics":[74,104],"across":[78,162],"different":[79,156],"In":[82],"this":[83],"paper,":[84],"we":[85],"propose":[86],"framework":[88,126,172],"based":[89],"our":[91],"Space\u2013Time-varying":[92],"(STVG)":[94],"formalism":[95],"which":[96],"utilizes":[97],"Whole-graph":[99],"model":[102],"such":[108,189],"that":[109],"evolution":[111],"materializes":[115],"time-varying":[118],"its":[121],"Projected":[122,153],"graphs.":[123],"The":[124,198],"STVG":[125,171],"provides":[127],"an":[128],"reduce":[131],"massively":[136],"changing":[137],"new":[140],"nodes":[141],"edges":[143],"arrive":[144],"every":[145],"second.":[146],"It":[147],"affords":[148],"capability":[150],"extract":[152,179],"time-windows":[157],"analyze":[159],"their":[160],"metrics":[161,188],"varying":[163],"We":[166],"demonstrate":[167],"how":[168],"proposed":[170],"can":[173],"exploited":[175],"identify":[177],"patterns":[181,202],"public":[183],"bus":[184,219],"transit":[185],"using":[187],"as":[190,211,213],"density,":[192,207],"volume":[193],"average":[195],"path":[196],"length.":[197],"results":[199],"reveal":[200],"overall":[205],"network":[206],"traffic":[208],"congestion":[209],"density":[210,215],"well":[212],"respect":[217],"movement":[220],"hourly,":[222],"daily":[223],"monthly":[225]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
