{"id":"https://openalex.org/W4319459101","doi":"https://doi.org/10.1109/tkde.2023.3243169","title":"Towards Lightweight and Automated Representation Learning System for Networks","display_name":"Towards Lightweight and Automated Representation Learning System for Networks","publication_year":2023,"publication_date":"2023-02-08","ids":{"openalex":"https://openalex.org/W4319459101","doi":"https://doi.org/10.1109/tkde.2023.3243169"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2023.3243169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3243169","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.07084","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002856991","display_name":"Yuyang Xie","orcid":"https://orcid.org/0000-0003-3152-1936"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuyang Xie","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083333630","display_name":"Jiezhong Qiu","orcid":"https://orcid.org/0000-0001-9514-0708"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiezhong Qiu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065818820","display_name":"Laxman Dhulipala","orcid":"https://orcid.org/0000-0003-0685-064X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Laxman Dhulipala","raw_affiliation_strings":["University of Maryland, College Park, MD, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053437305","display_name":"Wenjian Yu","orcid":"https://orcid.org/0000-0003-4897-7251"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjian Yu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044791875","display_name":"Jie Tang","orcid":"https://orcid.org/0000-0003-3487-4593"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112534230","display_name":"Richard Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Richard Peng","raw_affiliation_strings":["University of Waterloo, Waterloo, ON, Canada"],"affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100342202","display_name":"Chi Wang","orcid":"https://orcid.org/0000-0001-5610-5547"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chi Wang","raw_affiliation_strings":["Microsoft Researcht, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Researcht, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5002856991"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.3461,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6284859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"35","issue":"9","first_page":"9613","last_page":"9627"},"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":0.9894999861717224,"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/T11478","display_name":"Caching and Content Delivery","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.7337839603424072},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6883010864257812},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.616269588470459},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.5028447508811951},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4426252245903015},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34109923243522644},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27924633026123047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26556432247161865}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7337839603424072},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6883010864257812},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.616269588470459},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.5028447508811951},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4426252245903015},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34109923243522644},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27924633026123047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26556432247161865},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2023.3243169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3243169","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2302.07084","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.07084","pdf_url":"https://arxiv.org/pdf/2302.07084","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2302.07084","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.07084","pdf_url":"https://arxiv.org/pdf/2302.07084","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1040948671","display_name":null,"funder_award_id":"61836013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8474963640","display_name":null,"funder_award_id":"61872206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4319459101.pdf"},"referenced_works_count":82,"referenced_works":["https://openalex.org/W26556108","https://openalex.org/W55768394","https://openalex.org/W755406177","https://openalex.org/W1514107797","https://openalex.org/W1543897857","https://openalex.org/W1574269637","https://openalex.org/W1676380800","https://openalex.org/W1888005072","https://openalex.org/W1932742904","https://openalex.org/W1981032891","https://openalex.org/W1983193888","https://openalex.org/W2004026774","https://openalex.org/W2041836310","https://openalex.org/W2046253692","https://openalex.org/W2090891622","https://openalex.org/W2092720654","https://openalex.org/W2117756735","https://openalex.org/W2118585731","https://openalex.org/W2127503167","https://openalex.org/W2129575457","https://openalex.org/W2154851992","https://openalex.org/W2339338500","https://openalex.org/W2387462954","https://openalex.org/W2394933259","https://openalex.org/W2511364592","https://openalex.org/W2802440256","https://openalex.org/W2805516822","https://openalex.org/W2807021761","https://openalex.org/W2890410227","https://openalex.org/W2890855364","https://openalex.org/W2897858793","https://openalex.org/W2912516411","https://openalex.org/W2914833637","https://openalex.org/W2926442184","https://openalex.org/W2950366365","https://openalex.org/W2952402334","https://openalex.org/W2962711740","https://openalex.org/W2962756421","https://openalex.org/W2963601856","https://openalex.org/W2963979747","https://openalex.org/W2964015378","https://openalex.org/W2964297465","https://openalex.org/W2964361301","https://openalex.org/W2966694634","https://openalex.org/W2986486878","https://openalex.org/W3000405543","https://openalex.org/W3007813770","https://openalex.org/W3095118267","https://openalex.org/W3099403815","https://openalex.org/W3099866104","https://openalex.org/W3100848837","https://openalex.org/W3103311102","https://openalex.org/W3103995645","https://openalex.org/W3104097132","https://openalex.org/W3137081859","https://openalex.org/W3159506417","https://openalex.org/W3201719193","https://openalex.org/W4234988573","https://openalex.org/W4240827605","https://openalex.org/W4251344828","https://openalex.org/W4288567469","https://openalex.org/W4291474301","https://openalex.org/W4293651439","https://openalex.org/W4294170691","https://openalex.org/W4294351786","https://openalex.org/W4297571622","https://openalex.org/W4297733535","https://openalex.org/W4297776040","https://openalex.org/W6622177582","https://openalex.org/W6637172029","https://openalex.org/W6677656871","https://openalex.org/W6682691769","https://openalex.org/W6685688796","https://openalex.org/W6703685949","https://openalex.org/W6726873649","https://openalex.org/W6744557953","https://openalex.org/W6751796012","https://openalex.org/W6754929296","https://openalex.org/W6755635308","https://openalex.org/W6760755035","https://openalex.org/W6784331282","https://openalex.org/W6788106616"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W3121932492","https://openalex.org/W4232638561","https://openalex.org/W1997544008","https://openalex.org/W2389214306","https://openalex.org/W1607100495","https://openalex.org/W4235240664","https://openalex.org/W3004137470","https://openalex.org/W2965083567","https://openalex.org/W2932872266"],"abstract_inverted_index":{"We":[0,82],"propose":[1],"<sc":[2,69,196,221],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[3,70,197,222],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">LightNE":[4,71,198,223],"2.0</small>":[5,72,199,224],",":[6],"a":[7,27,95,113,142,181,243],"cost-effective,":[8],"scalable,":[9],"automated,":[10],"and":[11,39,62,80,125,134,153,166,176,179,183,212,234],"high-quality":[12],"network":[13,45,88],"embedding":[14,46,77,89],"system":[15],"that":[16,36,52,195],"scales":[17],"to":[18,32,87,100,120,132,156,203],"graphs":[19,253],"with":[20,47,65,230],"hundreds":[21],"of":[22,24,105,163,254],"billions":[23],"edges":[25,237],"on":[26,242],"single":[28],"machine.":[29],"In":[30],"contrast":[31],"the":[33,84,91,102,136],"mainstream":[34],"belief":[35],"distributed":[37],"architecture":[38],"GPUs":[40],"are":[41],"needed":[42],"for":[43,90,171,188],"large-scale":[44],"good":[48],"quality,":[49,57],"we":[50,53],"prove":[51],"can":[54,200,225],"achieve":[55,121],"higher":[56],"better":[58,219],"scalability,":[59],"lower":[60],"cost,":[61],"faster":[63,205,209,214],"runtime":[64],"shared-memory,":[66],"CPU-only":[67],"architecture.":[68],"combines":[73],"two":[74],"theoretically":[75],"grounded":[76],"methods":[78],"NetSMF":[79,106,216],"ProNE.":[81],"introduce":[83],"following":[85],"techniques":[86],"first":[92],"time:":[93],"(1)":[94],"newly":[96],"proposed":[97,172],"downsampling":[98],"method":[99],"reduce":[101],"sample":[103],"complexity":[104],"while":[107,217,246],"preserving":[108],"its":[109],"theoretical":[110],"advantages;":[111],"(2)":[112],"high-performance":[114],"parallel":[115,129],"graph":[116,229],"processing":[117],"stack":[118],"GBBS":[119],"high":[122],"memory":[123],"efficiency":[124,165],"scalability;":[126],"(3)":[127],"sparse":[128],"hash":[130],"table":[131],"aggregate":[133],"maintain":[135],"matrix":[137],"sparsifier":[138],"in":[139,161,238],"memory;":[140],"(4)":[141],"fast":[143,154,173,182],"randomized":[144,159,174],"singular":[145],"value":[146],"decomposition":[147],"(SVD)":[148],"enhanced":[149],"by":[150],"power":[151],"iteration":[152],"orthonormalization":[155],"improve":[157],"vanilla":[158],"SVD":[160,175],"terms":[162],"both":[164],"effectiveness;":[167],"(5)":[168],"Intel":[169],"MKL":[170],"spectral":[177],"propagation;":[178],"(6)":[180],"lightweight":[184],"AutoML":[185],"library":[186],"FLAML":[187],"automated":[189],"hyperparameter":[190],"tuning.":[191],"Experimental":[192],"results":[193],"show":[194],"be":[201],"up":[202],"84\u00d7":[204],"than":[206,210,215],"GraphVite,":[207],"30\u00d7":[208],"PBG":[211],"9\u00d7":[213],"delivering":[218],"performance.":[220],"embed":[226],"very":[227,251],"large":[228,252],"1.7":[231],"billion":[232,236],"nodes":[233],"124":[235],"half":[239],"an":[240],"hour":[241],"CPU":[244],"server,":[245],"other":[247],"baselines":[248],"cannot":[249],"handle":[250],"this":[255],"scale.":[256]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
