{"id":"https://openalex.org/W4386729899","doi":"https://doi.org/10.1145/3604915.3608863","title":"LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee\u2019s Advertisement Recommendation","display_name":"LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee\u2019s Advertisement Recommendation","publication_year":2023,"publication_date":"2023-09-14","ids":{"openalex":"https://openalex.org/W4386729899","doi":"https://doi.org/10.1145/3604915.3608863"},"language":"en","primary_location":{"id":"doi:10.1145/3604915.3608863","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604915.3608863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.19394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101961271","display_name":"Dang Minh Nguyen","orcid":"https://orcid.org/0000-0002-5951-7229"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dang Minh Nguyen","raw_affiliation_strings":["Shopee, Shopee, SEA Group, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-5951-7229","affiliations":[{"raw_affiliation_string":"Shopee, Shopee, SEA Group, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081174724","display_name":"Chenfei Wang","orcid":"https://orcid.org/0009-0004-8423-1136"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chenfei Wang","raw_affiliation_strings":["Shopee, SEA Group, Singapore"],"raw_orcid":"https://orcid.org/0009-0004-8423-1136","affiliations":[{"raw_affiliation_string":"Shopee, SEA Group, Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059137233","display_name":"Yan Shen","orcid":"https://orcid.org/0009-0000-5247-4150"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Shen","raw_affiliation_strings":["Shopee, SEA Group, Singapore"],"raw_orcid":"https://orcid.org/0009-0000-5247-4150","affiliations":[{"raw_affiliation_string":"Shopee, SEA Group, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069589795","display_name":"Yifan Zeng","orcid":"https://orcid.org/0009-0000-6143-3043"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifan Zeng","raw_affiliation_strings":["Shopee, SEA Group, China"],"raw_orcid":"https://orcid.org/0009-0000-6143-3043","affiliations":[{"raw_affiliation_string":"Shopee, SEA Group, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101961271"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1389,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.92904847,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"334","last_page":"337"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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"}},{"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/T10028","display_name":"Topic Modeling","score":0.994700014591217,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7906304597854614},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5760254859924316},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5457415580749512},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5442320704460144},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4988095760345459},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.44504380226135254},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.4388173818588257},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4298853278160095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42450541257858276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3582410216331482},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3580777049064636},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.238082617521286},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08513551950454712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7906304597854614},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5760254859924316},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5457415580749512},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5442320704460144},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4988095760345459},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.44504380226135254},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.4388173818588257},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4298853278160095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42450541257858276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3582410216331482},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3580777049064636},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.238082617521286},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08513551950454712},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3604915.3608863","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604915.3608863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2310.19394","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.19394","pdf_url":"https://arxiv.org/pdf/2310.19394","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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:figshare.com:article/24521938","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/LightSAGE_Graph_Neural_Networks_for_Large_Scale_Item_Retrieval_in_Shopee_s_Advertisement_Recommendation/24521938","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.19394","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.19394","pdf_url":"https://arxiv.org/pdf/2310.19394","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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386729899.pdf","grobid_xml":"https://content.openalex.org/works/W4386729899.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2807021761","https://openalex.org/W2911286998","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2963601856","https://openalex.org/W2964341035","https://openalex.org/W3004578093","https://openalex.org/W3036320503","https://openalex.org/W3045200674","https://openalex.org/W3093187255","https://openalex.org/W3094605801","https://openalex.org/W3098468692","https://openalex.org/W3100278010","https://openalex.org/W3100331887","https://openalex.org/W3100848837","https://openalex.org/W3104353018","https://openalex.org/W3153325943","https://openalex.org/W4226237846","https://openalex.org/W4285723986","https://openalex.org/W4294170691","https://openalex.org/W4294558607","https://openalex.org/W4296300780","https://openalex.org/W4300175872","https://openalex.org/W4315977496"],"related_works":["https://openalex.org/W2497939785","https://openalex.org/W2219931199","https://openalex.org/W2735929803","https://openalex.org/W4241927574","https://openalex.org/W2971083348","https://openalex.org/W3214288750","https://openalex.org/W584290403","https://openalex.org/W2786642545","https://openalex.org/W2084560547","https://openalex.org/W4315783862"],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Network":[2],"(GNN)":[3],"is":[4,65],"the":[5,33,38,41,52,56,158],"trending":[6],"solution":[7],"for":[8,67,122],"item":[9,70,95],"retrieval":[10,71],"in":[11,32,51,83,139,148],"recommendation":[12],"problems.":[13],"Most":[14],"recent":[15],"reports,":[16],"however,":[17],"focus":[18],"heavily":[19],"on":[20],"new":[21,112],"model":[22],"architectures.":[23],"This":[24],"may":[25],"bring":[26,146],"some":[27],"gaps":[28],"when":[29],"applying":[30],"GNN":[31,64,113],"industrial":[34],"setup,":[35],"where,":[36],"besides":[37],"model,":[39],"constructing":[40],"graph":[42,84],"and":[43,80,87,133,154],"handling":[44,88],"data":[45,89],"sparsity":[46],"also":[47],"play":[48],"critical":[49,138],"roles":[50],"overall":[53],"success":[54],"of":[55,161],"project.":[57],"In":[58],"this":[59],"work,":[60],"we":[61,92,126],"report":[62],"how":[63],"applied":[66],"large-scale":[68],"e-commerce":[69],"at":[72],"Shopee.":[73],"We":[74,108],"introduce":[75],"our":[76],"simple":[77],"yet":[78],"novel":[79],"impactful":[81],"techniques":[82],"construction,":[85],"modeling,":[86],"skewness.":[90],"Specifically,":[91],"construct":[93],"high-quality":[94,119],"graphs":[96],"by":[97],"combining":[98],"strong-signal":[99],"user":[100],"behaviors":[101],"with":[102],"high-precision":[103],"collaborative":[104],"filtering":[105],"(CF)":[106],"algorithm.":[107],"then":[109],"develop":[110],"a":[111],"architecture":[114],"named":[115],"LightSAGE":[116],"to":[117,130,157],"produce":[118],"items\u2019":[120],"embeddings":[121],"vector":[123],"search.":[124],"Finally,":[125],"design":[127],"multiple":[128],"strategies":[129],"handle":[131],"cold-start":[132],"long-tail":[134],"items,":[135],"which":[136],"are":[137,155],"an":[140],"advertisement":[141],"(ads)":[142],"system.":[143,165],"Our":[144],"models":[145],"improvement":[147],"offline":[149],"evaluations,":[150],"online":[151],"A/B":[152],"tests,":[153],"deployed":[156],"main":[159],"traffic":[160],"Shopee\u2019s":[162],"Recommendation":[163],"Advertisement":[164]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
