{"id":"https://openalex.org/W4312192824","doi":"https://doi.org/10.1080/0952813x.2022.2153270","title":"Attributed network embedding with dual fusion strategies","display_name":"Attributed network embedding with dual fusion strategies","publication_year":2022,"publication_date":"2022-12-22","ids":{"openalex":"https://openalex.org/W4312192824","doi":"https://doi.org/10.1080/0952813x.2022.2153270"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2022.2153270","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5000249151","display_name":"Kunjie Dong","orcid":"https://orcid.org/0000-0001-8340-7110"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunjie Dong","raw_affiliation_strings":["School of information, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of information, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653521","display_name":"Lihua Zhou","orcid":"https://orcid.org/0000-0002-8940-1155"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lihua Zhou","raw_affiliation_strings":["School of information, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of information, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048703431","display_name":"Tong Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Huang","raw_affiliation_strings":["School of information, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of information, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018736430","display_name":"Guowang Du","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guowang Du","raw_affiliation_strings":["School of information, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of information, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020614119","display_name":"Yiting Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I120825670","display_name":"Yunnan Normal University","ror":"https://ror.org/00sc9n023","country_code":"CN","type":"education","lineage":["https://openalex.org/I120825670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiting Jiang","raw_affiliation_strings":["School of information, Yunnan Normal University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of information, Yunnan Normal University, Kunming, China","institution_ids":["https://openalex.org/I120825670"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100653521"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"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":60},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9971,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9556,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.43609852},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4126871}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.826486},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.5231563},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.52109945},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5209688},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.51722443},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5052803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47246882},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.43609852},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.43010807},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4126871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37599733},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33504122},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20040753},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08682516},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","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},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2022.2153270","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61762090"}],"datasets":[],"versions":[],"referenced_works_count":35,"referenced_works":["https://openalex.org/W1059873271","https://openalex.org/W1888005072","https://openalex.org/W2004915807","https://openalex.org/W2090252637","https://openalex.org/W2090891622","https://openalex.org/W2162760472","https://openalex.org/W2301363727","https://openalex.org/W2393319904","https://openalex.org/W2607500032","https://openalex.org/W2622489478","https://openalex.org/W2767220239","https://openalex.org/W2804558096","https://openalex.org/W2808000122","https://openalex.org/W2808466528","https://openalex.org/W2897117569","https://openalex.org/W2908027240","https://openalex.org/W2950723285","https://openalex.org/W2962756421","https://openalex.org/W2963169753","https://openalex.org/W2963224980","https://openalex.org/W2963707260","https://openalex.org/W2963893312","https://openalex.org/W2964363216","https://openalex.org/W2965568863","https://openalex.org/W2966423701","https://openalex.org/W2998358581","https://openalex.org/W3089656492","https://openalex.org/W3104097132","https://openalex.org/W3137933686","https://openalex.org/W3143546659","https://openalex.org/W3145543370","https://openalex.org/W4206625749","https://openalex.org/W4220693589","https://openalex.org/W4232226726","https://openalex.org/W748373178"],"related_works":["https://openalex.org/W4383553409","https://openalex.org/W4372316851","https://openalex.org/W4285172739","https://openalex.org/W3139833644","https://openalex.org/W3123208392","https://openalex.org/W3123110765","https://openalex.org/W2521519254","https://openalex.org/W2212953222","https://openalex.org/W2104948296","https://openalex.org/W1735800226"],"abstract_inverted_index":{"Attributed":[0,104],"network":[1,8,22,28,49,144],"embedding":[2],"(ANE)":[3],"maps":[4],"nodes":[5],"in":[6,42,99],"a":[7,10,37],"into":[9],"low-dimensional":[11],"space":[12],"while":[13],"preserving":[14],"the":[15,43,73,90,94,126,135,152,161,169,190,195,205],"intrinsic":[16],"essence":[17],"of":[18,54,62,92,116,163,171,194,215],"node":[19,25,46,141,172,174],"attribute":[20,26,47,142],"and":[21,27,33,39,48,86,96,129,137,143,159,178,192,209],"topology.":[23,145],"Incorporating":[24],"topology":[29,50],"with":[30,108,168],"more":[31,34],"deeply":[32],"harmoniously":[35],"is":[36],"critical":[38],"challenging":[40],"issue":[41],"ANE,":[44,100],"because":[45],"are":[51,149],"two":[52,60,147],"kinds":[53,61],"heterogeneous":[55,63,164],"information.":[56,165],"Existing":[57],"approaches":[58],"fuse":[59],"information":[64,98,139,157],"at":[65,79],"different":[66,80],"stages:":[67],"i.e.":[68],"before,":[69],"during":[70,151],"or":[71],"after":[72],"learning":[74,153],"process.":[75],"In":[76],"fact,":[77],"fusions":[78],"stages":[81],"have":[82,185],"their":[83],"own":[84],"advantages":[85],"disadvantages.":[87],"To":[88],"maximise":[89],"profit":[91],"utilising":[93],"attributed":[95],"networked":[97],"we":[101],"propose":[102],"an":[103],"Network":[105],"Embedding":[106],"model":[107],"Dual":[109],"Fusion":[110],"strategies":[111],"(abbr.":[112],"ANEDF),":[113],"which":[114,155],"consists":[115],"both":[117],"mutually":[118],"beneficial":[119],"components:":[120],"early":[121],"fusion":[122,131],"component":[123,132],"for":[124,133],"capturing":[125],"latent":[127],"complementarity":[128],"late":[130],"extracting":[134],"unique":[136],"distinctive":[138],"from":[140],"The":[146,198],"components":[148],"co-trained":[150],"process,":[154],"promotes":[156],"interaction":[158],"captures":[160],"consensus":[162],"Extensive":[166],"experiments":[167],"tasks":[170],"classification,":[173,207],"clustering,":[175],"link":[176,210],"prediction":[177,211],"visualisation":[179],"on":[180,213],"eight":[181],"publicly":[182],"available":[183],"networks":[184],"been":[186],"conducted":[187],"to":[188],"evaluate":[189],"effectiveness":[191],"rationality":[193],"proposed":[196],"model.":[197],"experimental":[199],"results":[200],"demonstrate":[201],"that":[202],"ANEDF":[203],"obtains":[204],"best":[206],"clustering":[208],"performance":[212],"6\u20137":[214],"8":[216],"datasets,":[217],"respectively.":[218]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4312192824","counts_by_year":[],"updated_date":"2024-12-24T04:06:49.385887","created_date":"2023-01-04"}