{"id":"https://openalex.org/W2951284826","doi":"https://doi.org/10.1145/3292500.3330924","title":"Learning Network-to-Network Model for Content-rich Network Embedding","display_name":"Learning Network-to-Network Model for Content-rich Network Embedding","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2951284826","doi":"https://doi.org/10.1145/3292500.3330924","mag":"2951284826"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330924","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","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/A5101449608","display_name":"Zhicheng He","orcid":"https://orcid.org/0009-0004-1701-0990"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhicheng He","raw_affiliation_strings":["Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101603878","display_name":"Jie Liu","orcid":"https://orcid.org/0000-0001-5544-8417"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368082","display_name":"Na Li","orcid":"https://orcid.org/0000-0002-1909-6378"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Li","raw_affiliation_strings":["Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101082924","display_name":"Yalou Huang","orcid":"https://orcid.org/0000-0002-6573-1854"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalou Huang","raw_affiliation_strings":["Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101449608"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":1.0506,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82218826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1037","last_page":"1045"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9811000227928162,"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":0.9653000235557556,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7074846029281616},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.7072232365608215},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5038911700248718},{"id":"https://openalex.org/keywords/network-simulation","display_name":"Network simulation","score":0.45776110887527466},{"id":"https://openalex.org/keywords/network-formation","display_name":"Network formation","score":0.4526883363723755},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.4246806502342224},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.42215168476104736},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40887272357940674},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.37158769369125366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3231689929962158},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12132924795150757},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08290216326713562},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08188283443450928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074846029281616},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.7072232365608215},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5038911700248718},{"id":"https://openalex.org/C139940560","wikidata":"https://www.wikidata.org/wiki/Q290036","display_name":"Network simulation","level":2,"score":0.45776110887527466},{"id":"https://openalex.org/C68416499","wikidata":"https://www.wikidata.org/wiki/Q7001033","display_name":"Network formation","level":2,"score":0.4526883363723755},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.4246806502342224},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.42215168476104736},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40887272357940674},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.37158769369125366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3231689929962158},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12132924795150757},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08290216326713562},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08188283443450928},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330924","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1888005072","https://openalex.org/W2001141328","https://openalex.org/W2012909434","https://openalex.org/W2022322548","https://openalex.org/W2027824794","https://openalex.org/W2046868922","https://openalex.org/W2053186076","https://openalex.org/W2062797058","https://openalex.org/W2065153599","https://openalex.org/W2090891622","https://openalex.org/W2118111139","https://openalex.org/W2131744502","https://openalex.org/W2145658888","https://openalex.org/W2150461699","https://openalex.org/W2154851992","https://openalex.org/W2155461593","https://openalex.org/W2156718197","https://openalex.org/W2162630660","https://openalex.org/W2242161203","https://openalex.org/W2387462954","https://openalex.org/W2393319904","https://openalex.org/W2511871973","https://openalex.org/W2519887557","https://openalex.org/W2523246573","https://openalex.org/W2530041791","https://openalex.org/W2536880093","https://openalex.org/W2538371562","https://openalex.org/W2574817444","https://openalex.org/W2579372251","https://openalex.org/W2582993595","https://openalex.org/W2584620251","https://openalex.org/W2585247128","https://openalex.org/W2607500032","https://openalex.org/W2612872092","https://openalex.org/W2624431344","https://openalex.org/W2740934577","https://openalex.org/W2766453196","https://openalex.org/W2768352146","https://openalex.org/W2782733358","https://openalex.org/W2808867307","https://openalex.org/W2809156873","https://openalex.org/W2809219720","https://openalex.org/W2886594383","https://openalex.org/W2888221391","https://openalex.org/W2950577311","https://openalex.org/W2962756421","https://openalex.org/W2963224980","https://openalex.org/W2963460103","https://openalex.org/W3022413497","https://openalex.org/W3104097132","https://openalex.org/W3104717349","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W2357578125","https://openalex.org/W2380853618","https://openalex.org/W2371512349","https://openalex.org/W3099594505","https://openalex.org/W4386127589","https://openalex.org/W2610818021","https://openalex.org/W2475532212","https://openalex.org/W2060648632","https://openalex.org/W2378321236","https://openalex.org/W332864920"],"abstract_inverted_index":{"Recently,":[0],"network":[1,14,23,47,97,108,148,188,191],"embedding":[2,48,87],"(NE)":[3],"has":[4,17],"achieved":[5],"great":[6],"successes":[7],"in":[8,51,169,194],"learning":[9,33,174],"low":[10],"dimensional":[11],"representations":[12],"for":[13,35,89],"nodes":[15,39,123],"and":[16,57,81,109,121,141],"been":[18],"increasingly":[19],"applied":[20],"to":[21,124,137,160,181,189],"various":[22],"analytic":[24],"tasks.":[25],"In":[26],"this":[27],"paper,":[28],"we":[29,65,93],"consider":[30],"the":[31,53,58,63,79,95,114,118,122,139,145,150,162,175,184,199,205,222],"representation":[32],"problem":[34],"content-rich":[36,96],"networks":[37,102,220],"whose":[38],"are":[40],"associated":[41],"with":[42,103],"rich":[43,59],"content":[44,82,107,142,187],"information.":[45],"Content-rich":[46],"is":[49,127,135,158,192],"challenging":[50],"fusing":[52],"complex":[54],"structural":[55],"dependencies":[56],"contents.":[60],"To":[61],"tackle":[62],"challenges,":[64],"propose":[66],"a":[67,99,130,155,195],"generative":[68,196],"model,":[69,74],"Network-to-Network":[70],"Network":[71],"Embedding":[72],"(Net2Net-NE)":[73],"which":[75],"can":[76,207],"effectively":[77],"fuse":[78,138],"structure":[80,140],"information":[83,143],"into":[84,149,166],"one":[85],"continuous":[86],"vector":[88],"each":[90,178],"node.":[91],"Specifically,":[92],"regard":[94],"as":[98,210],"pair":[100],"of":[101,144,177,224],"different":[104],"modalities,":[105],"i.e.,":[106],"node":[110,120,152,164,167,179,190,212],"network.":[111,172],"By":[112,173],"exploiting":[113],"strong":[115],"correlation":[116],"between":[117],"focal":[119],"whom":[125],"it":[126],"connected":[128],"to,":[129],"multilayer":[131],"recursively":[132],"composable":[133],"encoder":[134],"proposed":[136],"entire":[146],"ego":[147],"egocentric":[151,163],"embedding.":[153],"Moreover,":[154],"cross-modal":[156],"decoder":[157],"deployed":[159],"mapping":[161,185],"embeddings":[165],"identities":[168],"an":[170],"interconnected":[171],"identity":[176],"according":[180],"its":[182],"content,":[183],"from":[186],"learned":[193,203],"manner.":[197],"Hence":[198],"latent":[200],"encoding":[201],"vectors":[202],"by":[204],"Net2Net-NE":[206,225],"be":[208],"used":[209],"effective":[211],"embeddings.":[213],"Extensive":[214],"experimental":[215],"results":[216],"on":[217],"three":[218],"real-world":[219],"demonstrate":[221],"superiority":[223],"over":[226],"state-of-the-art":[227],"methods.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}