{"id":"https://openalex.org/W4320024139","doi":"https://doi.org/10.1109/bigdata55660.2022.10020666","title":"bigg2vec: Fast and Memory-Efficient Representation Learning for Billion-Scale Graphs on a Single Machine","display_name":"bigg2vec: Fast and Memory-Efficient Representation Learning for Billion-Scale Graphs on a Single Machine","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4320024139","doi":"https://doi.org/10.1109/bigdata55660.2022.10020666"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020666","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020666","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5087350627","display_name":"Mangesh Bendre","orcid":"https://orcid.org/0009-0002-5945-304X"},"institutions":[{"id":"https://openalex.org/I4210148469","display_name":"Visa (United States)","ror":"https://ror.org/05t1y0b59","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148469"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mangesh Bendre","raw_affiliation_strings":["Visa Research,Palo Alto,CA,USA","Visa Research, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Visa Research,Palo Alto,CA,USA","institution_ids":["https://openalex.org/I4210148469"]},{"raw_affiliation_string":"Visa Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210148469"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008531526","display_name":"Mahashweta Das","orcid":"https://orcid.org/0000-0003-1714-1996"},"institutions":[{"id":"https://openalex.org/I4210148469","display_name":"Visa (United States)","ror":"https://ror.org/05t1y0b59","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahashweta Das","raw_affiliation_strings":["Visa Research,Palo Alto,CA,USA","Visa Research, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Visa Research,Palo Alto,CA,USA","institution_ids":["https://openalex.org/I4210148469"]},{"raw_affiliation_string":"Visa Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210148469"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000202397","display_name":"Vineeth Rakesh","orcid":"https://orcid.org/0000-0001-7586-0257"},"institutions":[{"id":"https://openalex.org/I4210148469","display_name":"Visa (United States)","ror":"https://ror.org/05t1y0b59","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vineeth Rakesh","raw_affiliation_strings":["Visa Research,Palo Alto,CA,USA","Visa Research, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Visa Research,Palo Alto,CA,USA","institution_ids":["https://openalex.org/I4210148469"]},{"raw_affiliation_string":"Visa Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210148469"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455958","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0003-3462-8472"},"institutions":[{"id":"https://openalex.org/I4210148469","display_name":"Visa (United States)","ror":"https://ror.org/05t1y0b59","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Visa Research,Palo Alto,CA,USA","Visa Research, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Visa Research,Palo Alto,CA,USA","institution_ids":["https://openalex.org/I4210148469"]},{"raw_affiliation_string":"Visa Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210148469"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038736812","display_name":"Hao Yang","orcid":"https://orcid.org/0000-0001-8861-7010"},"institutions":[{"id":"https://openalex.org/I4210148469","display_name":"Visa (United States)","ror":"https://ror.org/05t1y0b59","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Yang","raw_affiliation_strings":["Visa Research,Palo Alto,CA,USA","Visa Research, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Visa Research,Palo Alto,CA,USA","institution_ids":["https://openalex.org/I4210148469"]},{"raw_affiliation_string":"Visa Research, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I4210148469"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5087350627"],"corresponding_institution_ids":["https://openalex.org/I4210148469"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20572075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"abs/2101.08358","issue":null,"first_page":"835","last_page":"843"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9941999912261963,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/scalability","display_name":"Scalability","score":0.8555954694747925},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8394526839256287},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7506924867630005},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5908992886543274},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5335023403167725},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5313416719436646},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49253663420677185},{"id":"https://openalex.org/keywords/auxiliary-memory","display_name":"Auxiliary memory","score":0.48806679248809814},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.486741304397583},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4710034430027008},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44738367199897766},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4426823854446411},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4413440227508545},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4299720525741577},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.36388397216796875},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18550944328308105},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1423664391040802}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8555954694747925},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8394526839256287},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7506924867630005},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5908992886543274},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5335023403167725},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5313416719436646},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49253663420677185},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.48806679248809814},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.486741304397583},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4710034430027008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44738367199897766},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4426823854446411},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4413440227508545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4299720525741577},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.36388397216796875},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18550944328308105},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1423664391040802},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","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":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020666","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020666","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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":32,"referenced_works":["https://openalex.org/W8870360","https://openalex.org/W142088563","https://openalex.org/W1522888794","https://openalex.org/W1614298861","https://openalex.org/W1888005072","https://openalex.org/W1981025032","https://openalex.org/W2025789985","https://openalex.org/W2121050483","https://openalex.org/W2142535891","https://openalex.org/W2594833348","https://openalex.org/W2612872092","https://openalex.org/W2807021761","https://openalex.org/W2905441753","https://openalex.org/W2912516411","https://openalex.org/W2962756421","https://openalex.org/W2963988212","https://openalex.org/W3035403290","https://openalex.org/W3080456792","https://openalex.org/W3099403815","https://openalex.org/W3100848837","https://openalex.org/W3121826770","https://openalex.org/W3133886099","https://openalex.org/W4205113689","https://openalex.org/W4293651439","https://openalex.org/W6600367688","https://openalex.org/W6605647140","https://openalex.org/W6636510571","https://openalex.org/W6680402377","https://openalex.org/W6744557953","https://openalex.org/W6760045743","https://openalex.org/W6760755035","https://openalex.org/W6789019443"],"related_works":["https://openalex.org/W1967627035","https://openalex.org/W1800827217","https://openalex.org/W1531780705","https://openalex.org/W2370911386","https://openalex.org/W2116951845","https://openalex.org/W2040758634","https://openalex.org/W3207688490","https://openalex.org/W2943242083","https://openalex.org/W4323323198","https://openalex.org/W4320024139"],"abstract_inverted_index":{"Node":[0],"embeddings":[1,25,165,189,206],"obtained":[2],"from":[3],"information":[4,16],"networks":[5],"have":[6,40,160],"been":[7],"widely":[8],"adopted":[9],"for":[10,93,107,149,166,190],"representing":[11],"knowledge":[12],"and":[13,18,70,110,122,129],"driving":[14],"various":[15],"retrieval":[17],"machine":[19],"learning":[20],"tasks.":[21],"However,":[22],"training":[23,60,88,98,208],"node":[24],"is":[26,62,152,179],"computationally":[27],"intensive,":[28],"making":[29],"it":[30],"difficult":[31],"to":[32,34,56,63,136,163,186],"scale":[33],"larger":[35],"graphs.":[36],"Most":[37],"existing":[38],"works":[39],"addressed":[41],"the":[42,59,82,96,114,143],"scalability":[43,79],"challenge":[44],"by":[45,80,196],"simply":[46],"adding":[47],"more":[48,197],"hardware":[49],"resources.":[50],"For":[51],"example,":[52],"a":[53,102,132,215],"common":[54],"approach":[55,77],"speed":[57],"up":[58,95],"process":[61],"distribute":[64],"model":[65],"computation":[66,85],"across":[67],"multiple":[68,167],"machines":[69],"GPUs.":[71],"This":[72],"paper":[73],"takes":[74],"an":[75],"orthogonal":[76],"towards":[78],"addressing":[81],"problem":[83],"of":[84,145],"complexity":[86],"in":[87],"embeddings.":[89],"We":[90,159],"present":[91],"bigg2vec":[92,100,162,185,202],"scaling":[94],"embedding":[97,127],"process.":[99],"introduces":[101],"novel":[103,133],"polar":[104],"coordinate-based":[105],"system":[106],"internal":[108],"representation":[109],"computation.":[111],"It":[112,118],"provides":[113],"following":[115],"benefits:":[116],"(a)":[117],"significantly":[119],"reduces":[120,142],"compute":[121],"memory":[123],"requirements":[124],"while":[125,207],"improving":[126],"quality":[128,205],"(b)":[130],"uses":[131,184],"graph":[134],"organization":[135],"generate":[137,164,188],"high-quality":[138],"negative":[139,146],"samples":[140,147],"(this":[141],"number":[144],"needed":[148],"training,":[150],"which":[151],"especially":[153],"beneficial":[154],"f":[155],"or":[156],"skewed":[157],"graphs).":[158],"deployed":[161],"AI":[168],"models":[169],"within":[170],"Visa.":[171],"Our":[172],"Global":[173],"Personalized":[174],"Restaurant":[175],"Recommender":[176],"System":[177],"(GPR)":[178],"one":[180],"such":[181],"project":[182],"that":[183],"periodically":[187],"over":[191],"450":[192],"million":[193],"nodes":[194],"connected":[195],"than":[198,211],"3":[199],"billion":[200],"edges.":[201],"generates":[203],"higher":[204],"them":[209],"faster":[210],"state-of-the-art":[212],"methods":[213],"on":[214],"single":[216],"CPU-based":[217],"machine.":[218]},"counts_by_year":[],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}