{"id":"https://openalex.org/W4220740995","doi":"https://doi.org/10.1145/3517207.3526974","title":"Scaling knowledge graph embedding models for link prediction","display_name":"Scaling knowledge graph embedding models for link prediction","publication_year":2022,"publication_date":"2022-03-29","ids":{"openalex":"https://openalex.org/W4220740995","doi":"https://doi.org/10.1145/3517207.3526974"},"language":"en","primary_location":{"id":"doi:10.1145/3517207.3526974","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3517207.3526974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd European Workshop on Machine Learning and Systems","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/A5081488132","display_name":"Nasrullah Sheikh","orcid":"https://orcid.org/0000-0001-7194-9385"},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nasrullah Sheikh","raw_affiliation_strings":["IBM Research Almaden"],"affiliations":[{"raw_affiliation_string":"IBM Research Almaden","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100688602","display_name":"Qin Xiao","orcid":"https://orcid.org/0000-0002-6643-6400"},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Qin","raw_affiliation_strings":["IBM Research Almaden"],"affiliations":[{"raw_affiliation_string":"IBM Research Almaden","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036119025","display_name":"Berthold Reinwald","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Berthold Reinwald","raw_affiliation_strings":["IBM Research Almaden"],"affiliations":[{"raw_affiliation_string":"IBM Research Almaden","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004959524","display_name":"Chuan Lei","orcid":"https://orcid.org/0000-0001-6265-9554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chuan Lei","raw_affiliation_strings":["Instacart"],"affiliations":[{"raw_affiliation_string":"Instacart","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081488132"],"corresponding_institution_ids":["https://openalex.org/I4210085935"],"apc_list":null,"apc_paid":null,"fwci":0.6885,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73949469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"87","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980999827384949,"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":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/scaling","display_name":"Scaling","score":0.7155410647392273},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.6876775026321411},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6565176248550415},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6141687035560608},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4942303001880646},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.46129855513572693},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3892953097820282},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27936652302742004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1983667016029358},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08061543107032776}],"concepts":[{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.7155410647392273},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.6876775026321411},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6565176248550415},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6141687035560608},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4942303001880646},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.46129855513572693},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3892953097820282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27936652302742004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1983667016029358},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08061543107032776},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3517207.3526974","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3517207.3526974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd European Workshop on Machine Learning and Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W125936143","https://openalex.org/W2262682425","https://openalex.org/W2296407087","https://openalex.org/W2739716023","https://openalex.org/W2745138925","https://openalex.org/W2759136286","https://openalex.org/W2890187992","https://openalex.org/W2912500072","https://openalex.org/W2919278763","https://openalex.org/W2962953852","https://openalex.org/W2990947761","https://openalex.org/W3002924435","https://openalex.org/W3009233884","https://openalex.org/W3012000912","https://openalex.org/W3035403290","https://openalex.org/W3122741928","https://openalex.org/W3130062726","https://openalex.org/W3159953606"],"related_works":["https://openalex.org/W2923818335","https://openalex.org/W4226361842","https://openalex.org/W4310879833","https://openalex.org/W4312937211","https://openalex.org/W3138254819","https://openalex.org/W4312327654","https://openalex.org/W2979603757","https://openalex.org/W2784239688","https://openalex.org/W3103545790","https://openalex.org/W4221140418"],"abstract_inverted_index":{"Developing":[0],"scalable":[1],"solutions":[2],"for":[3,9,36,44,77],"training":[4,38],"Graph":[5],"Neural":[6],"Networks":[7],"(GNNs)":[8],"link":[10,45],"prediction":[11,46],"tasks":[12],"is":[13],"challenging":[14],"due":[15],"to":[16,47,97],"the":[17,56],"inherent":[18],"data":[19],"dependencies":[20],"which":[21],"entail":[22],"high":[23],"computational":[24],"costs":[25],"and":[26,65],"a":[27,33,84,93],"huge":[28],"memory":[29],"footprint.":[30],"We":[31],"propose":[32,55],"new":[34],"method":[35],"scaling":[37,75],"of":[39],"knowledge":[40,79],"graph":[41,80],"embedding":[42,81],"models":[43,82],"address":[48],"these":[49],"challenges.":[50],"Towards":[51],"this":[52],"end,":[53],"we":[54],"following":[57],"algorithmic":[58],"strategies:":[59],"self-sufficient":[60],"partitions,":[61],"constraint-based":[62],"negative":[63],"sampling,":[64],"edge":[66],"mini-batch":[67],"training.":[68],"The":[69],"experimental":[70],"evaluation":[71],"shows":[72],"that":[73],"our":[74],"solution":[76],"GNN-based":[78],"achieves":[83],"16x":[85],"speed":[86],"up":[87],"on":[88,100],"benchmark":[89],"datasets":[90],"while":[91],"maintaining":[92],"comparable":[94],"model":[95],"performance":[96],"non-distributed":[98],"methods":[99],"standard":[101],"metrics.":[102]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}