{"id":"https://openalex.org/W3049084953","doi":"https://doi.org/10.1155/2020/8845942","title":"Community Detection Based on DeepWalk Model in Large-Scale Networks","display_name":"Community Detection Based on DeepWalk Model in Large-Scale Networks","publication_year":2020,"publication_date":"2020-11-20","ids":{"openalex":"https://openalex.org/W3049084953","doi":"https://doi.org/10.1155/2020/8845942","mag":"3049084953"},"language":"en","primary_location":{"id":"doi:10.1155/2020/8845942","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/8845942","pdf_url":"https://downloads.hindawi.com/journals/scn/2020/8845942.pdf","source":{"id":"https://openalex.org/S120683614","display_name":"Security and Communication Networks","issn_l":"1939-0114","issn":["1939-0114","1939-0122"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Security and Communication Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/scn/2020/8845942.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009433750","display_name":"Yunfang Chen","orcid":"https://orcid.org/0000-0002-7897-3588"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfang Chen","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039493907","display_name":"Li Wang","orcid":"https://orcid.org/0000-0002-3198-5012"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078493269","display_name":"Dehao Qi","orcid":"https://orcid.org/0000-0001-5413-2269"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dehao Qi","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053920875","display_name":"Tinghuai Ma","orcid":"https://orcid.org/0000-0003-2320-1692"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tinghuai Ma","raw_affiliation_strings":["School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210-044, China"],"affiliations":[{"raw_affiliation_string":"School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210-044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084565580","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-1658-0236"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China","School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084565580"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":0.6662,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.67876185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2020","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9879000186920166,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9873999953269958,"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":0.8737892508506775},{"id":"https://openalex.org/keywords/community-structure","display_name":"Community structure","score":0.6665069460868835},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.624150812625885},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6200166940689087},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6002867221832275},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5786765217781067},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5725482106208801},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5133718252182007},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4777181148529053},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4552229642868042},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.45137208700180054},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4144747853279114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37429943680763245},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07900336384773254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8737892508506775},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.6665069460868835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.624150812625885},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6200166940689087},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6002867221832275},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5786765217781067},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5725482106208801},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5133718252182007},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4777181148529053},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4552229642868042},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.45137208700180054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4144747853279114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37429943680763245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07900336384773254},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2020/8845942","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/8845942","pdf_url":"https://downloads.hindawi.com/journals/scn/2020/8845942.pdf","source":{"id":"https://openalex.org/S120683614","display_name":"Security and Communication Networks","issn_l":"1939-0114","issn":["1939-0114","1939-0122"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Security and Communication Networks","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:adb9f4e603aa4c4397a6e6e45434d8b9","is_oa":true,"landing_page_url":"https://doaj.org/article/adb9f4e603aa4c4397a6e6e45434d8b9","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Security and Communication Networks, Vol 2020 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2020/8845942","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/8845942","pdf_url":"https://downloads.hindawi.com/journals/scn/2020/8845942.pdf","source":{"id":"https://openalex.org/S120683614","display_name":"Security and Communication Networks","issn_l":"1939-0114","issn":["1939-0114","1939-0122"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Security and Communication Networks","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6560771554","display_name":null,"funder_award_id":"U1736105","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7058848123","display_name":null,"funder_award_id":"61672297","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3049084953.pdf","grobid_xml":"https://content.openalex.org/works/W3049084953.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1486632395","https://openalex.org/W1587744656","https://openalex.org/W1614298861","https://openalex.org/W1888005072","https://openalex.org/W1942910215","https://openalex.org/W1971421925","https://openalex.org/W1990706897","https://openalex.org/W2030696657","https://openalex.org/W2032735940","https://openalex.org/W2033590892","https://openalex.org/W2120211304","https://openalex.org/W2127048411","https://openalex.org/W2127498532","https://openalex.org/W2149055390","https://openalex.org/W2154851992","https://openalex.org/W2161455936","https://openalex.org/W2375070860","https://openalex.org/W2393319904","https://openalex.org/W2466078306","https://openalex.org/W2513813309","https://openalex.org/W2538283942","https://openalex.org/W2556598943","https://openalex.org/W2604942799","https://openalex.org/W2745915530","https://openalex.org/W2885870007","https://openalex.org/W2894027578","https://openalex.org/W2904108909","https://openalex.org/W2915361359","https://openalex.org/W2924265866","https://openalex.org/W2933869810","https://openalex.org/W2947883071","https://openalex.org/W2948133842","https://openalex.org/W2962975498","https://openalex.org/W2962991892","https://openalex.org/W2965263145","https://openalex.org/W2977142280","https://openalex.org/W2991222574","https://openalex.org/W2996939444","https://openalex.org/W3033971658","https://openalex.org/W3101380508","https://openalex.org/W3102641634","https://openalex.org/W3104097132","https://openalex.org/W3106886494","https://openalex.org/W6712081154","https://openalex.org/W6736262870","https://openalex.org/W6785351508","https://openalex.org/W6936242187","https://openalex.org/W6948116018"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W1975321310","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2014494654","https://openalex.org/W2055243143","https://openalex.org/W3130349901","https://openalex.org/W2849310602","https://openalex.org/W1578916557"],"abstract_inverted_index":{"The":[0],"large-scale":[1,23,138],"and":[2,27,82,101],"complex":[3],"structure":[4,21],"of":[5,50,85,109,128],"real":[6],"networks":[7,24],"brings":[8],"enormous":[9],"challenges":[10],"to":[11,18,45,59,104],"traditional":[12],"community":[13,20,32,145,152],"detection":[14,33],"methods.":[15],"In":[16],"order":[17,44,103],"detect":[19],"in":[22,43,102,137],"more":[25,132],"accurately":[26],"efficiently,":[28],"we":[29],"propose":[30],"a":[31,61,80,89,96],"algorithm":[34],"based":[35],"on":[36,119],"the":[37,47,56,86,107,120,125,135,143,147,151],"network":[38,51,63],"embedding":[39],"representation":[40],"method.":[41],"Firstly,":[42],"solve":[46],"scarce":[48],"problem":[49],"data,":[52],"this":[53,129],"paper":[54,130],"uses":[55],"DeepWalk":[57],"model":[58,99,126],"embed":[60],"high-dimensional":[62],"into":[64,95,115],"low-dimensional":[65,71],"space":[66],"with":[67,75],"topology":[68],"information.":[69],"Then,":[70],"data":[72],"are":[73,93,153],"processed,":[74],"each":[76,83],"node":[77,87],"treated":[78],"as":[79,88],"sample":[81],"dimension":[84],"feature.":[90],"Finally,":[91],"samples":[92],"fed":[94],"Gaussian":[97],"mixture":[98],"(GMM),":[100],"automatically":[105],"learn":[106],"number":[108],"communities,":[110],"variational":[111],"inference":[112],"is":[113],"introduced":[114],"GMM.":[116],"Experimental":[117],"results":[118],"DBLP":[121],"dataset":[122],"show":[123],"that":[124],"method":[127],"can":[131],"effectively":[133],"discover":[134],"communities":[136],"networks.":[139],"By":[140],"further":[141],"analyzing":[142],"excavated":[144],"structure,":[146],"organizational":[148],"characteristics":[149],"within":[150],"better":[154],"revealed.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
