{"id":"https://openalex.org/W4412877184","doi":"https://doi.org/10.1145/3711896.3737026","title":"LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture","display_name":"LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture","publication_year":2025,"publication_date":"2025-08-03","ids":{"openalex":"https://openalex.org/W4412877184","doi":"https://doi.org/10.1145/3711896.3737026"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3737026","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737026","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737026","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737026","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"YanHui Li","orcid":"https://orcid.org/0009-0000-2180-9157"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"YanHui Li","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-2180-9157","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037566066","display_name":"Dongxia Wang","orcid":"https://orcid.org/0000-0001-9812-3911"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxia Wang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9812-3911","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033957641","display_name":"Zhu Sun","orcid":"https://orcid.org/0000-0002-3350-7022"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhu Sun","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-3350-7022","affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore, Singapore","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103325860","display_name":"Haonan Zhang","orcid":"https://orcid.org/0009-0009-9782-4121"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haonan Zhang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0009-9782-4121","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101350512","display_name":"Huizhong Guo","orcid":"https://orcid.org/0009-0004-0011-8612"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huizhong Guo","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-0011-8612","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":2.4025,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90279961,"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":"1577","last_page":"1588"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T11478","display_name":"Caching and Content Delivery","score":0.9940000176429749,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9904999732971191,"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":0.7763723134994507},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.701395571231842},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.35458824038505554},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.062197744846343994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7763723134994507},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.701395571231842},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.35458824038505554},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.062197744846343994},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3711896.3737026","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737026","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737026","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2506.10347","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.10347","pdf_url":"https://arxiv.org/pdf/2506.10347","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doi:10.1145/3711896.3737026","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3737026","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3737026","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412877184.pdf","grobid_xml":"https://content.openalex.org/works/W4412877184.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W2509893387","https://openalex.org/W2792839191","https://openalex.org/W2884134047","https://openalex.org/W2912351665","https://openalex.org/W2913560138","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2963911286","https://openalex.org/W2979683452","https://openalex.org/W3045200674","https://openalex.org/W3095602948","https://openalex.org/W3098087397","https://openalex.org/W3100278010","https://openalex.org/W3106439716","https://openalex.org/W3113410469","https://openalex.org/W3114652457","https://openalex.org/W3129482887","https://openalex.org/W3152893301","https://openalex.org/W3155919942","https://openalex.org/W3203626883","https://openalex.org/W4212975546","https://openalex.org/W4224914537","https://openalex.org/W4225412853","https://openalex.org/W4225816397","https://openalex.org/W4283065823","https://openalex.org/W4283379500","https://openalex.org/W4306316988","https://openalex.org/W4309765757","https://openalex.org/W4321485535","https://openalex.org/W4379931871","https://openalex.org/W4383604692","https://openalex.org/W4392384521","https://openalex.org/W4392944481","https://openalex.org/W4396216288","https://openalex.org/W4400524564","https://openalex.org/W4403791433","https://openalex.org/W4409365786","https://openalex.org/W6606275768","https://openalex.org/W6784694379"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2038503502"],"abstract_inverted_index":{"Recently,":[0],"Graph":[1],"Neural":[2],"Networks":[3],"(GNNs)":[4],"have":[5],"become":[6],"the":[7,33,52,137,154,161,198],"dominant":[8],"approach":[9],"for":[10],"Knowledge":[11],"Graph-aware":[12],"Recommender":[13],"Systems":[14],"(KGRSs)":[15],"due":[16],"to":[17,31,37,49,57,73,108,148,216],"their":[18,59],"proven":[19],"effectiveness.":[20],"Building":[21],"upon":[22],"GNN-based":[23,54,106],"KGRSs,":[24,51],"Self-Supervised":[25],"Learning":[26],"(SSL)":[27],"has":[28],"been":[29],"incorporated":[30],"address":[32,109],"sparity":[34],"issue,":[35],"leading":[36],"longer":[38],"training":[39,193,213],"time.":[40,194],"However,":[41],"through":[42],"extensive":[43],"experiments,":[44],"we":[45,99],"reveal":[46],"that:":[47],"(1)compared":[48],"other":[50],"existing":[53],"KGRSs":[55,183,217],"fail":[56],"keep":[58],"superior":[60],"performance":[61],"under":[62],"sparse":[63,77,186],"interactions":[64],"even":[65],"with":[66,218],"SSL.":[67,150,219],"(2)":[68],"More":[69],"complex":[70,81],"models":[71],"tend":[72],"perform":[74],"worse":[75],"in":[76,157,168,184,206],"interaction":[78],"scenarios":[79,189],"and":[80,129,165,187,209],"mechanisms,":[82],"like":[83],"attention":[84],"mechanism,":[85],"can":[86],"be":[87],"detrimental":[88],"as":[89,122],"they":[90],"often":[91],"increase":[92],"learning":[93],"difficulty.":[94],"Inspired":[95],"by":[96,201],"these":[97],"findings,":[98],"propose":[100],"LightKG,":[101],"a":[102,114,131],"simple":[103],"yet":[104],"powerful":[105],"KGRS":[107],"sparsity":[110],"issues.":[111],"LightKG":[112,142,179],"includes":[113],"simplified":[115],"GNN":[116],"layer":[117,147],"that":[118,178],"encodes":[119],"directed":[120],"relations":[121],"scalar":[123],"pairs":[124],"rather":[125],"than":[126],"dense":[127,188],"embeddings":[128],"employs":[130],"linear":[132],"aggregation":[133],"framework,":[134],"greatly":[135],"reducing":[136,192],"complexity":[138],"of":[139,204,212],"GNNs.":[140],"Additionally,":[141],"incorporates":[143],"an":[144,202],"efficient":[145],"contrastive":[146],"implement":[149],"It":[151],"directly":[152],"minimizes":[153],"node":[155],"similarity":[156],"original":[158],"graph,":[159],"avoiding":[160],"time-consuming":[162],"subgraph":[163],"generation":[164],"comparison":[166],"required":[167],"previous":[169],"SSL":[170],"methods.":[171],"Experiments":[172],"on":[173],"four":[174],"benchmark":[175],"datasets":[176],"show":[177],"outperforms":[180],"12":[181],"competitive":[182],"both":[185],"while":[190],"significantly":[191],"Specifically,":[195],"it":[196],"surpasses":[197],"best":[199],"baselines":[200],"average":[203],"5.8%":[205],"recommendation":[207],"accuracy":[208],"saves":[210],"84.3%":[211],"time":[214],"compared":[215],"Our":[220],"code":[221],"is":[222],"available":[223],"at":[224],"https://github.com/1371149/LightKG.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-07T08:38:57.713557","created_date":"2025-10-10T00:00:00"}
