{"id":"https://openalex.org/W3005316051","doi":"https://doi.org/10.1109/access.2020.2971968","title":"Node Similarity Measure in Directed Weighted Complex Network Based on Node Nearest Neighbor Local Network Relative Weighted Entropy","display_name":"Node Similarity Measure in Directed Weighted Complex Network Based on Node Nearest Neighbor Local Network Relative Weighted Entropy","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3005316051","doi":"https://doi.org/10.1109/access.2020.2971968","mag":"3005316051"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2971968","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2971968","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08985350.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08985350.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025962504","display_name":"Wanchang Jiang","orcid":"https://orcid.org/0000-0002-5924-5403"},"institutions":[{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanchang Jiang","raw_affiliation_strings":["School of Computer Science, Northeast Electric Power University, Jilin, China"],"raw_orcid":"https://orcid.org/0000-0002-5924-5403","affiliations":[{"raw_affiliation_string":"School of Computer Science, Northeast Electric Power University, Jilin, China","institution_ids":["https://openalex.org/I179060312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100443399","display_name":"Yinghui Wang","orcid":"https://orcid.org/0000-0002-9837-1226"},"institutions":[{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghui Wang","raw_affiliation_strings":["School of Computer Science, Northeast Electric Power University, Jilin, China"],"raw_orcid":"https://orcid.org/0000-0002-9837-1226","affiliations":[{"raw_affiliation_string":"School of Computer Science, Northeast Electric Power University, Jilin, China","institution_ids":["https://openalex.org/I179060312"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I179060312"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5588,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.82276804,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"32432","last_page":"32441"},"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9940999746322632,"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":0.992900013923645,"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":0.6191666126251221},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5955483913421631},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5806804299354553},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5763126015663147},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5086442232131958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5033449530601501},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.488591730594635},{"id":"https://openalex.org/keywords/weighted-network","display_name":"Weighted network","score":0.45919692516326904},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45899325609207153},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43223822116851807},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.42001429200172424},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36226168274879456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33886873722076416},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09919074177742004}],"concepts":[{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6191666126251221},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5955483913421631},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5806804299354553},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5763126015663147},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5086442232131958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5033449530601501},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.488591730594635},{"id":"https://openalex.org/C142323842","wikidata":"https://www.wikidata.org/wiki/Q7979900","display_name":"Weighted network","level":3,"score":0.45919692516326904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45899325609207153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43223822116851807},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.42001429200172424},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36226168274879456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33886873722076416},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09919074177742004},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2971968","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2971968","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08985350.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1becb4832ac64de5bc43c5ee7601c00c","is_oa":true,"landing_page_url":"https://doaj.org/article/1becb4832ac64de5bc43c5ee7601c00c","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":"IEEE Access, Vol 8, Pp 32432-32441 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2971968","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2971968","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08985350.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G4739227733","display_name":"\u8f6f\u4ef6\u7cfb\u7edf\u590d\u6742\u7f51\u7edc\u5c42\u6b21\u5316\u5b9e\u4f53\u6316\u6398\u65b9\u6cd5\u53ca\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61572420","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6129798006","display_name":null,"funder_award_id":"JJKH20190706KJ","funder_id":"https://openalex.org/F4320326270","funder_display_name":"Education Department of Jilin Province"},{"id":"https://openalex.org/G6861887101","display_name":null,"funder_award_id":"20190104140","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6875011876","display_name":null,"funder_award_id":"JJKH20190706KJ","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"},{"id":"https://openalex.org/F4320322174","display_name":"People's Government of Jilin Province","ror":"https://ror.org/02fzqav45"},{"id":"https://openalex.org/F4320326270","display_name":"Education Department of Jilin Province","ror":"https://ror.org/05782e512"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3005316051.pdf","grobid_xml":"https://content.openalex.org/works/W3005316051.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1994106452","https://openalex.org/W2019935267","https://openalex.org/W2024982571","https://openalex.org/W2050287748","https://openalex.org/W2072072903","https://openalex.org/W2077744535","https://openalex.org/W2381000297","https://openalex.org/W2708425986","https://openalex.org/W2739963493","https://openalex.org/W2761803352","https://openalex.org/W2769582432","https://openalex.org/W2797028873","https://openalex.org/W3003676657","https://openalex.org/W3112745662"],"related_works":["https://openalex.org/W3087005418","https://openalex.org/W2367848132","https://openalex.org/W2368799136","https://openalex.org/W2170666601","https://openalex.org/W2046676475","https://openalex.org/W3113796761","https://openalex.org/W2889984455","https://openalex.org/W2005073207","https://openalex.org/W2931395331","https://openalex.org/W2360586622"],"abstract_inverted_index":{"Node":[0,82,111,154,166,204],"similarity":[1,35,47,182,189,248,258],"is":[2,49,74,87,114,162,184,207],"a":[3,44,102,179],"significant":[4],"basis":[5,78],"for":[6,169],"analyzing":[7],"features":[8,91],"in":[9,95,124,144,195,249],"complex":[10,13,71,122,198,232],"network.":[11],"For":[12],"network":[14,60,72,86,98,126,147],"with":[15,107,245],"directed":[16,69,196],"weighted":[17,62,70,197],"edge,":[18],"the":[19,22,27,38,53,77,81,96,118,135,145,151,171,188,202,216,221,238,246,250,256],"complexity":[20],"of":[21,29,41,55,79,92,104,120,142,153,193,220,226],"relationship":[23,30,123],"among":[24],"nodes":[25,143,194,244,259],"and":[26,66,140,200,218],"diversity":[28],"weights":[31],"make":[32],"measure":[33,48,183,187,239],"node":[34,46,56,94,128,149,181],"complicated":[36],"from":[37,260],"huge":[39],"amounts":[40],"nodes.":[42,177,213],"Therefore,":[43],"novel":[45,180],"proposed":[50,208,222],"based":[51,68],"on":[52,76,127,230],"design":[54],"nearest":[57],"neighbor":[58],"local":[59,97,125,146],"relative":[61],"entropy.":[63],"Firstly,":[64],"degree":[65,139],"strength":[67,141],"model":[73],"constructed,":[75],"that,":[80],"Nearest":[83,155],"Neighbor":[84,156],"Local":[85,157],"defined.":[88],"The":[89,234],"structural":[90,121,172],"each":[93],"are":[99],"quantized":[100],"into":[101],"set":[103],"decision":[105],"probabilities":[106],"multiple":[108],"indicators.":[109],"Furthermore,":[110],"Connection":[112],"Tightness":[113],"given":[115],"to":[116,132,164,186,209],"compute":[117],"influence":[119],"similarity.":[129],"And":[130],"then,":[131],"evaluate":[133],"how":[134],"outward":[136],"&":[137],"inward":[138],"affect":[148],"similarity,":[150],"concept":[152],"Network":[158],"Relative":[159,167],"Weighted":[160],"Entropy":[161],"designed":[163,185],"define":[165],"Difference":[168],"measuring":[170],"difference":[173],"between":[174,190],"any":[175,191],"two":[176,224],"Accordingly,":[178],"pair":[192],"network,":[199],"then":[201],"Similar":[203],"Mining":[205],"Algorithm":[206],"obtain":[210],"most":[211,247,257],"similar":[212],"To":[214],"clarify":[215],"availability":[217],"effectiveness":[219],"measure,":[223],"sets":[225],"experiments":[227],"were":[228],"conducted":[229],"real-world":[231],"networks.":[233],"results":[235],"show":[236],"that":[237],"can":[240],"not":[241],"only":[242],"mine":[243,255],"same":[251],"module,":[252],"but":[253],"also":[254],"different":[261],"modules.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}