{"id":"https://openalex.org/W1987810983","doi":"https://doi.org/10.1145/2556195.2556225","title":"Learning latent representations of nodes for classifying in heterogeneous social networks","display_name":"Learning latent representations of nodes for classifying in heterogeneous social networks","publication_year":2014,"publication_date":"2014-02-18","ids":{"openalex":"https://openalex.org/W1987810983","doi":"https://doi.org/10.1145/2556195.2556225","mag":"1987810983"},"language":"en","primary_location":{"id":"doi:10.1145/2556195.2556225","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2556195.2556225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM international conference on Web search and data mining","raw_type":"proceedings-article"},"type":"preprint","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/A5054491937","display_name":"Yann Jacob","orcid":null},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210159731","display_name":"LIP6","ror":"https://ror.org/05krcen59","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159245","https://openalex.org/I4210159731"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Yann Jacob","raw_affiliation_strings":["Sorbonne Universites, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France"],"affiliations":[{"raw_affiliation_string":"Sorbonne Universites, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I39804081","https://openalex.org/I4210159731"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027101473","display_name":"Ludovic Denoyer","orcid":null},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210159731","display_name":"LIP6","ror":"https://ror.org/05krcen59","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159245","https://openalex.org/I4210159731"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ludovic Denoyer","raw_affiliation_strings":["Sorbonne Universites, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France"],"affiliations":[{"raw_affiliation_string":"Sorbonne Universites, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I39804081","https://openalex.org/I4210159731"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113667126","display_name":"Patrick Gallinari","orcid":"https://orcid.org/0000-0003-3360-8269"},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210159731","display_name":"LIP6","ror":"https://ror.org/05krcen59","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159245","https://openalex.org/I4210159731"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Patrick Gallinari","raw_affiliation_strings":["Sorbonne Universites, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France"],"affiliations":[{"raw_affiliation_string":"Sorbonne Universites, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France","institution_ids":["https://openalex.org/I204730241","https://openalex.org/I39804081","https://openalex.org/I4210159731"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054491937"],"corresponding_institution_ids":["https://openalex.org/I204730241","https://openalex.org/I39804081","https://openalex.org/I4210159731"],"apc_list":null,"apc_paid":null,"fwci":12.3058,"has_fulltext":false,"cited_by_count":114,"citation_normalized_percentile":{"value":0.9862119,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"373","last_page":"382"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9991999864578247,"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/T10028","display_name":"Topic Modeling","score":0.9868000149726868,"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":0.749927282333374},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6925306916236877},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6917737722396851},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6177213788032532},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.544124186038971},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5348417162895203},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4959500730037689},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.4546854496002197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4517313241958618},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43266212940216064},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.43227308988571167},{"id":"https://openalex.org/keywords/social-network-analysis","display_name":"Social network analysis","score":0.43016698956489563},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4045320451259613},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36605358123779297},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14055708050727844},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.07900258898735046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.749927282333374},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6925306916236877},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6917737722396851},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6177213788032532},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.544124186038971},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5348417162895203},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4959500730037689},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.4546854496002197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4517313241958618},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43266212940216064},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.43227308988571167},{"id":"https://openalex.org/C114713312","wikidata":"https://www.wikidata.org/wiki/Q7551269","display_name":"Social network analysis","level":3,"score":0.43016698956489563},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4045320451259613},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36605358123779297},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14055708050727844},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.07900258898735046},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"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:10.1145/2556195.2556225","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2556195.2556225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM international conference on Web search and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-01212733v1","is_oa":false,"landing_page_url":"https://hal.science/hal-01212733","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"The 7th ACM international conference on Web search and data mining, Feb 2014, New York City, United States. pp.373--382, &#x27E8;10.1145/2556195.2556225&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W61101988","https://openalex.org/W72451212","https://openalex.org/W103340358","https://openalex.org/W1497163089","https://openalex.org/W1534979469","https://openalex.org/W1548361610","https://openalex.org/W1571637021","https://openalex.org/W1753206028","https://openalex.org/W1995813622","https://openalex.org/W2010921004","https://openalex.org/W2018984973","https://openalex.org/W2045791652","https://openalex.org/W2095609079","https://openalex.org/W2095646393","https://openalex.org/W2102848467","https://openalex.org/W2104290444","https://openalex.org/W2104324457","https://openalex.org/W2117080111","https://openalex.org/W2132368295","https://openalex.org/W2137793309","https://openalex.org/W2145554761","https://openalex.org/W2149288670","https://openalex.org/W2152755144","https://openalex.org/W2153959628","https://openalex.org/W2154455818","https://openalex.org/W2156954687","https://openalex.org/W2165922980","https://openalex.org/W2184575469","https://openalex.org/W2247119764","https://openalex.org/W2997701990","https://openalex.org/W6682494755","https://openalex.org/W6686076552"],"related_works":["https://openalex.org/W2294667518","https://openalex.org/W2952662149","https://openalex.org/W2793616590","https://openalex.org/W2017710739","https://openalex.org/W2183090405","https://openalex.org/W2075666982","https://openalex.org/W2065835655","https://openalex.org/W3160699245","https://openalex.org/W2782955270","https://openalex.org/W2349928170"],"abstract_inverted_index":{"Social":[0],"networks":[1,30,43],"are":[2,46,81],"heterogeneous":[3,42,73],"systems":[4],"composed":[5],"of":[6,9,36,67,79,136,143,150],"different":[7,77,109,161],"types":[8,78],"nodes":[10,68,80,124],"(e.g.":[11,18],"users,":[12],"content,":[13],"groups,":[14],"etc.)":[15],"and":[16,25,44,48,70,153,157,173,178],"relations":[17],"social":[19,74],"or":[20,89],"similarity":[21],"relations).":[22],"While":[23],"learning":[24,98],"performing":[26],"inference":[27],"on":[28,41,147,169],"homogeneous":[29,59],"have":[31],"motivated":[32],"a":[33,94,102],"large":[34],"amount":[35],"research,":[37],"few":[38],"work":[39],"exists":[40],"there":[45],"open":[47],"challenging":[49],"issues":[50],"for":[51,58,97],"existing":[52],"methods":[53,145,177],"that":[54],"were":[55],"previously":[56],"developed":[57],"networks.":[60],"We":[61,92],"address":[62],"here":[63],"the":[64,108,127,144,155,160],"specific":[65],"problem":[66],"classification":[69],"tagging":[71],"in":[72,116,126],"networks,":[75],"where":[76],"considered,":[82],"each":[83],"type":[84],"with":[85],"its":[86],"own":[87],"label":[88],"tag":[90],"set.":[91],"propose":[93],"new":[95],"method":[96,166],"node":[99,110,162],"representations":[100,134],"onto":[101],"latent":[103,118],"space,":[104],"common":[105],"to":[106,131,175,179],"all":[107],"types.":[111,138,163],"Inference":[112],"is":[113,167],"then":[114],"performed":[115],"this":[117,121],"space.":[119],"In":[120],"framework,":[122],"two":[123,170],"connected":[125],"network":[128],"will":[129],"tend":[130],"share":[132],"similar":[133],"regardless":[135],"their":[137],"This":[139],"allows":[140],"bypassing":[141],"limitations":[142],"based":[146],"direct":[148],"extensions":[149],"homogenous":[151],"frameworks":[152],"exploiting":[154],"dependencies":[156],"correlations":[158],"between":[159],"The":[164],"proposed":[165],"tested":[168],"representative":[171],"datasets":[172],"compared":[174],"state-of-the-art":[176],"baselines.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
