{"id":"https://openalex.org/W3207377746","doi":"https://doi.org/10.1145/3491206","title":"Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding","display_name":"Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding","publication_year":2022,"publication_date":"2022-01-18","ids":{"openalex":"https://openalex.org/W3207377746","doi":"https://doi.org/10.1145/3491206","mag":"3207377746"},"language":"en","primary_location":{"id":"doi:10.1145/3491206","doi":"https://doi.org/10.1145/3491206","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3491206","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-a","jufo-3","ki-jl-2","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2110.07582","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102728193","display_name":"Jingya Zhou","orcid":"https://orcid.org/0000-0003-0721-7424","observed_orcids":["https://orcid.org/0000-0003-0721-7424"]},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingya Zhou","raw_affiliation_strings":["Soochow University, China Georgia Institute of Technology, Suzhou, Jiangsu, China, USA State Key Laboratory of Mathematical Engineering and Advanced Computing, Wuxi, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0003-0721-7424","affiliations":[{"raw_affiliation_string":"Soochow University, China Georgia Institute of Technology, Suzhou, Jiangsu, China, USA State Key Laboratory of Mathematical Engineering and Advanced Computing, Wuxi, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100343991","display_name":"Ling Liu","orcid":"https://orcid.org/0000-0002-4138-3082","observed_orcids":["https://orcid.org/0000-0002-4138-3082"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ling Liu","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069331320","display_name":"Wenqi Wei","orcid":"https://orcid.org/0000-0001-9177-114X","observed_orcids":["https://orcid.org/0000-0001-9177-114X"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenqi Wei","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022101610","display_name":"Jianxi Fan","orcid":"https://orcid.org/0000-0002-7055-5891","observed_orcids":["https://orcid.org/0000-0002-7055-5891"]},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxi Fan","raw_affiliation_strings":["Soochow University, Suzhou, Jiangsu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.5061,"has_fulltext":true,"cited_by_count":117,"citation_normalized_percentile":{"value":0.97853601,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":87,"max":100},"biblio":{"volume":"55","issue":"2","first_page":"1","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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":0.0,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/network-representation-learning","display_name":"network representation learning","score":1.0},{"id":"https://openalex.org/keywords/node-embeddings","display_name":"node embeddings","score":0.9070000052452087},{"id":"https://openalex.org/keywords/homogeneous-networks","display_name":"homogeneous networks","score":0.8330000042915344},{"id":"https://openalex.org/keywords/graph-mining","display_name":"graph mining","score":0.5899999737739563},{"id":"https://openalex.org/keywords/social-networks","display_name":"social networks","score":0.6930000185966492},{"id":"https://openalex.org/keywords/knowledge-graphs","display_name":"knowledge graphs","score":0.9850000143051147},{"id":"https://openalex.org/keywords/biomedical-networks","display_name":"biomedical networks","score":0.6570000052452087},{"id":"https://openalex.org/keywords/link-prediction","display_name":"link prediction","score":0.6840000152587891},{"id":"https://openalex.org/keywords/node-clustering","display_name":"node clustering","score":0.9959999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8032172322273254},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.678943395614624},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6661311984062195},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5443839430809021},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5036816000938416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45163047313690186},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4397149384021759},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4275439977645874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36176279187202454},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34363919496536255},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3491206","doi":"https://doi.org/10.1145/3491206","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3491206","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-a","jufo-3","ki-jl-2","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2110.07582","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.07582","pdf_url":"https://arxiv.org/pdf/2110.07582","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2110.07582","doi":"https://doi.org/10.48550/arxiv.2110.07582","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2110.07582","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2110.07582","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.07582","pdf_url":"https://arxiv.org/pdf/2110.07582","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G2264344241","display_name":"\u57fa\u4e8e\u7ebf\u6027\u7f16\u7801\u7684\u5b89\u5168\u9ad8\u6548\u8fb9\u7f18\u534f\u540c\u8ba1\u7b97\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"62072321","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3093446196","display_name":null,"funder_award_id":"2038029","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4875579843","display_name":null,"funder_award_id":"U1905211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5206010609","display_name":"TWC: Medium: Privacy Preserving Computation in Big Data Clouds","funder_award_id":"1564097","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6374073843","display_name":"EAGER: SaTC-EDU: Privacy Enhancing Techniques and Innovations for AI-Cybersecurity Cross Training","funder_award_id":"2038029","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G727974632","display_name":null,"funder_award_id":"61972272, 62172291, 62072321, and U1905211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7718165558","display_name":"\u591a\u6e90\u5f02\u8d28\u793e\u4ea4\u7f51\u7edc\u878d\u5408\u4e0e\u8425\u9500\u5f71\u54cd\u529b\u4f20\u64ad\u4f18\u5316\u7814\u7a76","funder_award_id":"61972272","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8330442010","display_name":null,"funder_award_id":"62172291","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309321","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324720","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3207377746.pdf","grobid_xml":"https://content.openalex.org/works/W3207377746.grobid-xml"},"referenced_works_count":116,"referenced_works":["https://openalex.org/W36903255","https://openalex.org/W1614298861","https://openalex.org/W1662382123","https://openalex.org/W1854214752","https://openalex.org/W1888005072","https://openalex.org/W1894439495","https://openalex.org/W1978400666","https://openalex.org/W2036380454","https://openalex.org/W2078841894","https://openalex.org/W2090891622","https://openalex.org/W2097308346","https://openalex.org/W2099471712","https://openalex.org/W2130306094","https://openalex.org/W2138204974","https://openalex.org/W2145658888","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2154872931","https://openalex.org/W2156718197","https://openalex.org/W2158787690","https://openalex.org/W2163605009","https://openalex.org/W2184957013","https://openalex.org/W2242161203","https://openalex.org/W2393319904","https://openalex.org/W2415243320","https://openalex.org/W2468907370","https://openalex.org/W2519887557","https://openalex.org/W2525778437","https://openalex.org/W2554952599","https://openalex.org/W2581887665","https://openalex.org/W2604942799","https://openalex.org/W2607500032","https://openalex.org/W2614812929","https://openalex.org/W2622849676","https://openalex.org/W2624431344","https://openalex.org/W2700550412","https://openalex.org/W2737925311","https://openalex.org/W2751808960","https://openalex.org/W2755092149","https://openalex.org/W2766453196","https://openalex.org/W2767500585","https://openalex.org/W2767834929","https://openalex.org/W2770604839","https://openalex.org/W2787927827","https://openalex.org/W2788045146","https://openalex.org/W2788379054","https://openalex.org/W2788512147","https://openalex.org/W2788614083","https://openalex.org/W2788816357","https://openalex.org/W2788921726","https://openalex.org/W2792234394","https://openalex.org/W2792690596","https://openalex.org/W2798932700","https://openalex.org/W2803303416","https://openalex.org/W2808466528","https://openalex.org/W2808867307","https://openalex.org/W2809156873","https://openalex.org/W2886594383","https://openalex.org/W2890855364","https://openalex.org/W2894175828","https://openalex.org/W2897245732","https://openalex.org/W2900252255","https://openalex.org/W2903036385","https://openalex.org/W2905410270","https://openalex.org/W2907192581","https://openalex.org/W2907492528","https://openalex.org/W2909137510","https://openalex.org/W2912516411","https://openalex.org/W2914721378","https://openalex.org/W2918992089","https://openalex.org/W2919997401","https://openalex.org/W2926442184","https://openalex.org/W2943373497","https://openalex.org/W2945266622","https://openalex.org/W2949559065","https://openalex.org/W2950393809","https://openalex.org/W2950723285","https://openalex.org/W2950777612","https://openalex.org/W2954442758","https://openalex.org/W2962756421","https://openalex.org/W2962767366","https://openalex.org/W2962779748","https://openalex.org/W2962975498","https://openalex.org/W2963169753","https://openalex.org/W2963224980","https://openalex.org/W2963359213","https://openalex.org/W2963410212","https://openalex.org/W2963456618","https://openalex.org/W2963460103","https://openalex.org/W2963555845","https://openalex.org/W2963564796","https://openalex.org/W2963603080","https://openalex.org/W2964282455","https://openalex.org/W2964418074","https://openalex.org/W2964544183","https://openalex.org/W2964565637","https://openalex.org/W2964767742","https://openalex.org/W2965568863","https://openalex.org/W2966050677","https://openalex.org/W2970132321","https://openalex.org/W2976859544","https://openalex.org/W2979250009","https://openalex.org/W2979535968","https://openalex.org/W2997058986","https://openalex.org/W3000752730","https://openalex.org/W3003265726","https://openalex.org/W3008778157","https://openalex.org/W3015606043","https://openalex.org/W3040043284","https://openalex.org/W3044897978","https://openalex.org/W3102972033","https://openalex.org/W3103995645","https://openalex.org/W3163842339","https://openalex.org/W4288278932","https://openalex.org/W4291474301","https://openalex.org/W6950194991"],"related_works":["https://openalex.org/W2886594383","https://openalex.org/W2896808365","https://openalex.org/W2781318495","https://openalex.org/W2943009035","https://openalex.org/W2896824970","https://openalex.org/W2993584982","https://openalex.org/W3118486513","https://openalex.org/W4306653209","https://openalex.org/W3131107316","https://openalex.org/W3139466607"],"abstract_inverted_index":{"Network":[0],"representation":[1],"learning":[2,36,60,102,153],"(NRL)":[3],"advances":[4],"the":[5,29,46,66,70,82,99,138,149,180],"conventional":[6],"graph":[7],"mining":[8],"of":[9,22,32,53,84,148,167,183],"social":[10],"networks,":[11,41],"knowledge":[12],"graphs,":[13],"and":[14,17,50,57,69,97,115,128,142,161,178,186],"complex":[15],"biomedical":[16],"physics":[18],"information":[19],"networks.":[20,79],"Dozens":[21],"NRL":[23,76,122,169,184],"algorithms":[24,185],"have":[25],"been":[26],"reported":[27],"in":[28,45],"literature.":[30],"Most":[31],"them":[33],"focus":[34],"on":[35,104],"node":[37,54,61,72,86,100,111,116,129,150],"embeddings":[38],"for":[39,59,75,120,176],"homogeneous":[40,78],"but":[42,171],"they":[43],"differ":[44],"specific":[47,51],"encoding":[48],"schemes":[49],"types":[52],"semantics":[55],"captured":[56],"used":[58,144],"embedding.":[62],"This":[63,155],"article":[64],"reviews":[65],"design":[67],"principles":[68],"different":[71,85,146,168],"embedding":[73,87,101,117,151],"techniques":[74,143,170],"over":[77],"To":[80],"facilitate":[81],"comparison":[83],"algorithms,":[88],"we":[89,136],"introduce":[90],"a":[91,105],"unified":[92],"reference":[93,134],"framework":[94],"to":[95],"divide":[96],"generalize":[98],"process":[103],"given":[106],"network":[107],"into":[108],"preprocessing":[109],"steps,":[110,114],"feature":[112],"extraction":[113],"model":[118,152],"training":[119],"an":[121,164],"task":[123],"such":[124],"as":[125],"link":[126],"prediction":[127],"clustering.":[130],"With":[131],"this":[132],"unifying":[133],"framework,":[135],"highlight":[137],"representative":[139],"methods,":[140],"models,":[141],"at":[145],"stages":[147],"process.":[154],"survey":[156],"not":[157],"only":[158],"helps":[159],"researchers":[160],"practitioners":[162],"gain":[163],"in-depth":[165],"understanding":[166],"also":[172],"provides":[173],"practical":[174],"guidelines":[175],"designing":[177],"developing":[179],"next":[181],"generation":[182],"systems.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":18},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":32},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2021-10-25T00:00:00"}
