{"id":"https://openalex.org/W2902690700","doi":"https://doi.org/10.1109/icpr.2018.8545109","title":"LHONE: Label Homophily Oriented Network Embedding","display_name":"LHONE: Label Homophily Oriented Network Embedding","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902690700","doi":"https://doi.org/10.1109/icpr.2018.8545109","mag":"2902690700"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"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/A5100350641","display_name":"Le Zhang","orcid":"https://orcid.org/0000-0003-0894-9651"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Le Zhang","raw_affiliation_strings":["School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100771932","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0002-9487-4643"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100718017","display_name":"Xiang Ji","orcid":"https://orcid.org/0000-0002-7234-6460"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Xiang","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060820237","display_name":"Qi Ying","orcid":"https://orcid.org/0000-0002-4560-433X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Qi","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100350641"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14162681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"290","issue":null,"first_page":"665","last_page":"670"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9957000017166138,"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":0.9957000017166138,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9746000170707703,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9628999829292297,"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/homophily","display_name":"Homophily","score":0.9785906672477722},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7082734704017639},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.658663272857666},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6146822571754456},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5294456481933594},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.5023674964904785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4309813976287842},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42820584774017334},{"id":"https://openalex.org/keywords/network-formation","display_name":"Network formation","score":0.4122706353664398},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17166325449943542},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.1629611849784851},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14644819498062134}],"concepts":[{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.9785906672477722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7082734704017639},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.658663272857666},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6146822571754456},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5294456481933594},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.5023674964904785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4309813976287842},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42820584774017334},{"id":"https://openalex.org/C68416499","wikidata":"https://www.wikidata.org/wiki/Q7001033","display_name":"Network formation","level":2,"score":0.4122706353664398},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17166325449943542},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.1629611849784851},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14644819498062134},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2018.8545109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"mag:3162306841","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201802275118063673","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W19838944","https://openalex.org/W1614298861","https://openalex.org/W1888005072","https://openalex.org/W2049633694","https://openalex.org/W2053186076","https://openalex.org/W2093402979","https://openalex.org/W2130354913","https://openalex.org/W2153635508","https://openalex.org/W2154851992","https://openalex.org/W2393319904","https://openalex.org/W2427862964","https://openalex.org/W2508137831","https://openalex.org/W2517417371","https://openalex.org/W2574817444","https://openalex.org/W2579372251","https://openalex.org/W2583803680","https://openalex.org/W2604942799","https://openalex.org/W2606315856","https://openalex.org/W2739946816","https://openalex.org/W2740934577","https://openalex.org/W2743104969","https://openalex.org/W2767849480","https://openalex.org/W2950577311","https://openalex.org/W2962756421","https://openalex.org/W2962904108","https://openalex.org/W2964154748","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W3142588439","https://openalex.org/W6726226389","https://openalex.org/W6731976766","https://openalex.org/W6732461846","https://openalex.org/W6736262870","https://openalex.org/W6736820733"],"related_works":["https://openalex.org/W4389650376","https://openalex.org/W3000882491","https://openalex.org/W2588686890","https://openalex.org/W2155299640","https://openalex.org/W3123562051","https://openalex.org/W2317657874","https://openalex.org/W2547959112","https://openalex.org/W3126117860","https://openalex.org/W2982395253","https://openalex.org/W2743277954"],"abstract_inverted_index":{"Network":[0,132],"embedding":[1,179],"is":[2,39,57],"to":[3,48,59,99,102,121,136,149,176],"learn":[4],"effective":[5],"low-dimensional":[6],"vector":[7,45,65,155],"representations":[8,66,156],"for":[9],"nodes":[10,95],"in":[11,19,42,67],"a":[12,68,108,111,127,145,159],"network":[13,29,112,148,178],"and":[14,32,51,153],"has":[15],"attracted":[16],"considerable":[17],"attention":[18],"recent":[20],"years.":[21],"To":[22,72],"date,":[23],"existing":[24],"methods":[25],"mainly":[26],"focus":[27],"on":[28,84,166],"structure":[30],"information":[31,62,82],"cannot":[33],"leverage":[34],"abundant":[35],"label":[36,54,61,81,86,89,141],"information,":[37,55],"which":[38],"potentially":[40],"valuable":[41],"learning":[43,154],"better":[44],"representations.":[46],"Due":[47],"the":[49,64,78,85,138,171],"noise":[50],"incompleteness":[52],"of":[53,80,110,140,173],"it":[56],"intractable":[58],"integrate":[60],"into":[63,113],"partially":[69,146],"labeled":[70,147],"network.":[71],"address":[73],"this":[74],"issue,":[75],"we":[76,125],"investigate":[77],"effects":[79],"based":[83],"homophily.":[87],"Briefly,":[88],"homophily":[90,142],"can":[91],"not":[92],"only":[93],"drive":[94],"sharing":[96],"similar":[97],"labels":[98],"be":[100],"connected":[101,120],"each":[103,122],"other,":[104],"but":[105],"also":[106],"produce":[107],"division":[109],"densely-connected,":[114],"homogeneous":[115],"parts":[116],"that":[117],"are":[118],"weakly":[119],"other.":[123],"Furthermore,":[124],"propose":[126],"novel":[128],"Label":[129],"Homophily":[130],"Oriented":[131],"Embedding":[133],"(LHONE)":[134],"model":[135,162],"make":[137],"best":[139],"by":[143],"converting":[144],"two":[150,167],"bipartite":[151],"networks,":[152],"combined":[157],"with":[158],"Gaussian":[160],"mixture":[161],"(GMM).":[163],"Extensive":[164],"experiments":[165],"real-world":[168],"networks":[169],"demonstrate":[170],"effectiveness":[172],"LHONE":[174],"compared":[175],"state-of-the-art":[177],"approaches.":[180]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
