{"id":"https://openalex.org/W2798908418","doi":"https://doi.org/10.1145/3209978.3210023","title":"Attentive Recurrent Social Recommendation","display_name":"Attentive Recurrent Social Recommendation","publication_year":2018,"publication_date":"2018-06-27","ids":{"openalex":"https://openalex.org/W2798908418","doi":"https://doi.org/10.1145/3209978.3210023","mag":"2798908418"},"language":"en","primary_location":{"id":"doi:10.1145/3209978.3210023","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3209978.3210023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval","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/A5054609020","display_name":"Peijie Sun","orcid":"https://orcid.org/0000-0001-9733-0521"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peijie Sun","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033706423","display_name":"Le Wu","orcid":"https://orcid.org/0000-0003-4556-0581"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Wu","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100377147","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-3094-7735"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Wang","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054609020"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":37.2595,"has_fulltext":false,"cited_by_count":128,"citation_normalized_percentile":{"value":0.99713066,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"185","last_page":"194"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9613999724388123,"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":0.9587000012397766,"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":0.788133978843689},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7821762561798096},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6422464847564697},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.641738772392273},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5290250778198242},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5280476212501526},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.4886341691017151},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.4518709182739258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4075717329978943},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3708985149860382},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3488580584526062},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.2949061989784241},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.234142005443573}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.788133978843689},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7821762561798096},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6422464847564697},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.641738772392273},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5290250778198242},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5280476212501526},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.4886341691017151},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.4518709182739258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4075717329978943},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3708985149860382},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3488580584526062},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.2949061989784241},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.234142005443573},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3209978.3210023","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3209978.3210023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G4306688910","display_name":null,"funder_award_id":"61432019, 61732008, 61725203,61602147,61632007)","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5589099401","display_name":null,"funder_award_id":"Grant No. 1708085QF155","funder_id":"https://openalex.org/F4320334897","funder_display_name":"Natural Science Foundation of Anhui Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334897","display_name":"Natural Science Foundation of Anhui Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W20066928","https://openalex.org/W1500188831","https://openalex.org/W1514535095","https://openalex.org/W1560267311","https://openalex.org/W1905882502","https://openalex.org/W1984069252","https://openalex.org/W1984189333","https://openalex.org/W1993897382","https://openalex.org/W2001344462","https://openalex.org/W2009837099","https://openalex.org/W2027135291","https://openalex.org/W2033198212","https://openalex.org/W2039613841","https://openalex.org/W2054141820","https://openalex.org/W2057763140","https://openalex.org/W2073926352","https://openalex.org/W2076219102","https://openalex.org/W2095705004","https://openalex.org/W2100755716","https://openalex.org/W2102937240","https://openalex.org/W2109742433","https://openalex.org/W2124142520","https://openalex.org/W2128272608","https://openalex.org/W2135598826","https://openalex.org/W2137245235","https://openalex.org/W2140310134","https://openalex.org/W2144487656","https://openalex.org/W2145094598","https://openalex.org/W2146456494","https://openalex.org/W2147880316","https://openalex.org/W2171279286","https://openalex.org/W2171960770","https://openalex.org/W2202083088","https://openalex.org/W2267735350","https://openalex.org/W2293634267","https://openalex.org/W2474909202","https://openalex.org/W2583674722","https://openalex.org/W2587290924","https://openalex.org/W2605350416","https://openalex.org/W2618530766","https://openalex.org/W2626473670","https://openalex.org/W2740063619","https://openalex.org/W2741249238","https://openalex.org/W2949888546","https://openalex.org/W2963323306","https://openalex.org/W2963895127","https://openalex.org/W2964052347","https://openalex.org/W4301312111","https://openalex.org/W6660309285"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2735929803","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W135044020","https://openalex.org/W2103058005"],"abstract_inverted_index":{"Collaborative":[0],"filtering(CF)":[1],"is":[2,196],"one":[3],"of":[4,77,108,236,269],"the":[5,15,52,57,59,67,71,75,87,106,143,169,200,207,228,237,241,253,267,275],"most":[6],"popular":[7],"techniques":[8],"for":[9,31,91,101,138,252],"building":[10],"recommender":[11],"systems.":[12],"To":[13,124],"alleviate":[14],"data":[16],"sparsity":[17],"issue":[18],"in":[19,127,168,247],"CF,":[20],"social":[21,27,68,72,88,98,103,112,117,140,159,178,202,223,230,255],"recommendation":[22,33,93,118,256],"has":[23],"emerged":[24],"by":[25,44,157,219],"leveraging":[26],"influence":[28,69,99,113,160,203,231],"among":[29,161,232],"users":[30,162],"better":[32],"performance.":[34],"In":[35,56,142,206],"these":[36],"systems,":[37],"users'":[38,63,78,148,185],"preferences":[39,79,154,239,243],"over":[40,80,155,189,204],"time":[41,156],"are":[42,244],"determined":[43],"their":[45],"temporal":[46,92,116,139,193,201,254],"dynamic":[47,150,170,177,238],"interests":[48,65,188],"as":[49,51],"well":[50],"general":[53,152,208],"static":[54,97,102,153,209,217,222,242],"interests.":[55],"meantime,":[58],"complex":[60,149,186],"interplay":[61],"between":[62],"internal":[64],"and":[66,151,240],"from":[70],"network":[73,89,135,182,195,225],"drives":[74],"evolution":[76],"time.":[81,205],"Nevertheless,":[82],"traditional":[83],"approaches":[84],"either":[85],"neglected":[86],"structure":[90],"or":[94],"assumed":[95],"a":[96,176,192,221,248],"strength":[100],"recommendation.":[104,141],"Thus,":[105],"problem":[107],"how":[109],"to":[110,114,183,198,226,274],"leverage":[111],"enhance":[115],"performance":[119],"remains":[120],"pretty":[121],"much":[122],"open.":[123],"this":[125,128],"end,":[126],"paper,":[129],"we":[130,146,174,213],"present":[131],"an":[132],"attentive":[133],"recurrent":[134,180],"based":[136],"approach":[137],"proposed":[144,197,271],"approach,":[145],"model":[147,227,272],"fusing":[158],"with":[163],"two":[164,262],"attention":[165,194,224],"networks.":[166],"Specifically,":[167],"preference":[171,210],"modeling":[172,211],"process,":[173,212],"design":[175],"aware":[179],"neural":[181],"capture":[184],"latent":[187],"time,":[190],"where":[191],"learn":[199],"characterize":[214],"each":[215],"user's":[216],"interest":[218],"introducing":[220],"stationary":[229],"users.":[233],"The":[234],"output":[235],"combined":[245],"together":[246],"unified":[249],"end-to-end":[250],"framework":[251],"task.":[257],"Finally,":[258],"experimental":[259],"results":[260],"on":[261],"real-world":[263],"datasets":[264],"clearly":[265],"show":[266],"superiority":[268],"our":[270],"compared":[273],"baselines.":[276]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}