{"id":"https://openalex.org/W4386730245","doi":"https://doi.org/10.1145/3604915.3608815","title":"Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation","display_name":"Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation","publication_year":2023,"publication_date":"2023-09-14","ids":{"openalex":"https://openalex.org/W4386730245","doi":"https://doi.org/10.1145/3604915.3608815"},"language":"en","primary_location":{"id":"doi:10.1145/3604915.3608815","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604915.3608815","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":"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/A5003106644","display_name":"Dugang Liu","orcid":"https://orcid.org/0000-0003-3612-709X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dugang Liu","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101398010","display_name":"Yuhao Wu","orcid":"https://orcid.org/0000-0003-2165-7303"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Wu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102820471","display_name":"Weixin Li","orcid":"https://orcid.org/0009-0006-9449-2596"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixin Li","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103197292","display_name":"Xiaolian Zhang","orcid":"https://orcid.org/0000-0002-9641-2848"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolian Zhang","raw_affiliation_strings":["Huawei 2012 Lab, China"],"affiliations":[{"raw_affiliation_string":"Huawei 2012 Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103256429","display_name":"Hao Wang","orcid":"https://orcid.org/0009-0005-3370-9424"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Huawei 2012 Lab, China"],"affiliations":[{"raw_affiliation_string":"Huawei 2012 Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045682499","display_name":"Qinjuan Yang","orcid":"https://orcid.org/0000-0002-3621-5965"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinjuan Yang","raw_affiliation_strings":["Huawei 2012 Lab, China"],"affiliations":[{"raw_affiliation_string":"Huawei 2012 Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633973","display_name":"Zhong Ming","orcid":"https://orcid.org/0000-0001-9310-3460"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Ming","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5003106644"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":2.265,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.9049141,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"588","last_page":"598"},"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":0.9966999888420105,"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/T12488","display_name":"Mental Health via Writing","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.791000485420227},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7806677222251892},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5908045768737793},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5599485635757446},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.531444251537323},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42163020372390747},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41482385993003845},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3567606806755066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3364025950431824},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32199087738990784}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.791000485420227},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7806677222251892},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5908045768737793},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5599485635757446},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.531444251537323},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42163020372390747},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41482385993003845},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3567606806755066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3364025950431824},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32199087738990784}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604915.3608815","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3604915.3608815","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1769245271","display_name":null,"funder_award_id":"62272315","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G407513521","display_name":null,"funder_award_id":"61836005, 62272315, 62172283","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G686898326","display_name":null,"funder_award_id":"62172283","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7097245526","display_name":null,"funder_award_id":"61836005","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1998889130","https://openalex.org/W2002834872","https://openalex.org/W2009385725","https://openalex.org/W2030385985","https://openalex.org/W2054141820","https://openalex.org/W2102937240","https://openalex.org/W2184957013","https://openalex.org/W2509893387","https://openalex.org/W2547424360","https://openalex.org/W2793768763","https://openalex.org/W2893775232","https://openalex.org/W2896691185","https://openalex.org/W2911778742","https://openalex.org/W2945623882","https://openalex.org/W2951661358","https://openalex.org/W2963323306","https://openalex.org/W2963911286","https://openalex.org/W2966349618","https://openalex.org/W3003875435","https://openalex.org/W3012780388","https://openalex.org/W3021904157","https://openalex.org/W3034364571","https://openalex.org/W3034601175","https://openalex.org/W3044893918","https://openalex.org/W3083824577","https://openalex.org/W3088364587","https://openalex.org/W3104030692","https://openalex.org/W3104763847","https://openalex.org/W3129482887","https://openalex.org/W3132016049","https://openalex.org/W3155919942","https://openalex.org/W3163986299","https://openalex.org/W3204808432","https://openalex.org/W4225412853","https://openalex.org/W4226380897","https://openalex.org/W4231054948","https://openalex.org/W4284672936","https://openalex.org/W4284675146","https://openalex.org/W4290875571"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4390273403","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W4386781444","https://openalex.org/W1692008701","https://openalex.org/W1968265719"],"abstract_inverted_index":{"Although":[0],"knowledge":[1,60,173],"graph":[2,52,72,82,129],"has":[3],"shown":[4],"their":[5],"effectiveness":[6,211],"in":[7,11,18,43],"mitigating":[8],"data":[9],"sparsity":[10,26,35],"many":[12],"recommendation":[13,177,193],"tasks,":[14],"they":[15],"remain":[16],"underutilized":[17],"context-aware":[19],"recommender":[20],"systems":[21],"(CARS)":[22],"with":[23,29,179],"the":[24,30,117,136,141,170,180,187,210],"specific":[25],"challenges":[27],"associated":[28],"contextual":[31,109,121],"features,":[32],"i.e.,":[33],"feature":[34],"and":[36,90,108,111,120,167,172,212],"interaction":[37],"sparsity.":[38],"To":[39],"bridge":[40],"this":[41,44],"gap,":[42],"paper,":[45],"we":[46,200],"propose":[47],"a":[48,71,79,125,145,158,176],"novel":[49],"pairwise":[50,80,126],"intent":[51,81,95,102,107,127,154],"embedding":[53],"learning":[54],"(PING)":[55],"framework":[56],"to":[57,77,134,160,185,195,208],"efficiently":[58,161],"integrate":[59],"graphs":[61],"into":[62],"CARS.":[63],"Specifically,":[64],"our":[65,215],"PING":[66],"contains":[67],"three":[68,205],"modules:":[69],"1)":[70],"construction":[73],"module":[74,131,178],"is":[75,132,183],"used":[76,133,184],"obtain":[78,135],"(PIG)":[83],"containing":[84],"nodes":[85,96],"for":[86],"users,":[87],"items,":[88],"entities,":[89],"enhanced":[91,94,153],"intent,":[92,110],"where":[93,151],"are":[97,114],"generated":[98],"by":[99,143],"applying":[100],"user":[101],"fusion":[103],"(UIF)":[104],"on":[105,149,204],"relational":[106],"two":[112],"sub-intents":[113],"derived":[115],"from":[116],"semantic":[118],"information":[119,163],"information,":[122],"respectively;":[123],"2)":[124],"joint":[128],"convolution":[130,147],"refined":[137,181],"embeddings":[138,182,190],"of":[139,191,214],"all":[140,169],"features":[142,166,171],"executing":[144],"customized":[146],"strategy":[148],"PIG,":[150],"each":[152],"node":[155],"acts":[156],"as":[157],"hub":[159],"propagate":[162],"among":[164],"different":[165],"between":[168],"graph;":[174],"3)":[175],"replace":[186],"randomly":[188],"initialized":[189],"downstream":[192],"models":[194],"improve":[196],"model":[197],"performance.":[198],"Finally,":[199],"conduct":[201],"extensive":[202],"experiments":[203],"public":[206],"datasets":[207],"verify":[209],"compatibility":[213],"PING.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}