{"id":"https://openalex.org/W3213484722","doi":"https://doi.org/10.1145/3459637.3482443","title":"Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation","display_name":"Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3213484722","doi":"https://doi.org/10.1145/3459637.3482443","mag":"3213484722"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482443","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","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/A5101631516","display_name":"Zeyuan Chen","orcid":"https://orcid.org/0000-0002-0286-6196"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeyuan Chen","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441646","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-4972-9594"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087158377","display_name":"Junchi Yan","orcid":"https://orcid.org/0000-0001-9639-7679"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junchi Yan","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367403","display_name":"Gang Wang","orcid":"https://orcid.org/0000-0002-7266-2412"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Wang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100630868","display_name":"Jianyong Wang","orcid":"https://orcid.org/0000-0002-7555-170X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyong Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101631516"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":5.7835,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.96205779,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"231","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9929999709129333,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9800000190734863,"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":0.8495678305625916},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5877164006233215},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5374157428741455},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5232462286949158},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5109121203422546},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4959131181240082},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49200984835624695},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.48653140664100647},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.4745933711528778},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46655744314193726},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46177753806114197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4421427249908447},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3365946412086487},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32143130898475647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8495678305625916},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5877164006233215},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5374157428741455},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5232462286949158},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5109121203422546},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4959131181240082},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49200984835624695},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.48653140664100647},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.4745933711528778},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46655744314193726},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46177753806114197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4421427249908447},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3365946412086487},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32143130898475647},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482443","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2008886893","https://openalex.org/W2061212083","https://openalex.org/W2069849731","https://openalex.org/W2509830164","https://openalex.org/W2583674722","https://openalex.org/W2605350416","https://openalex.org/W2625746539","https://openalex.org/W2739273093","https://openalex.org/W2783272285","https://openalex.org/W2788114581","https://openalex.org/W2789084759","https://openalex.org/W2807021761","https://openalex.org/W2809112621","https://openalex.org/W2886209086","https://openalex.org/W2899457523","https://openalex.org/W2902940626","https://openalex.org/W2914721378","https://openalex.org/W2923964967","https://openalex.org/W2945772520","https://openalex.org/W2945827670","https://openalex.org/W2950416221","https://openalex.org/W2965683718","https://openalex.org/W2985880542","https://openalex.org/W2996931760","https://openalex.org/W2998116985","https://openalex.org/W2998640320","https://openalex.org/W3012705926","https://openalex.org/W3031331881","https://openalex.org/W3034329572","https://openalex.org/W3034714642","https://openalex.org/W3045200674","https://openalex.org/W3080292067","https://openalex.org/W3080292238","https://openalex.org/W3088869197","https://openalex.org/W3094541400","https://openalex.org/W3094559936","https://openalex.org/W3098231197","https://openalex.org/W3100278010","https://openalex.org/W3100848837","https://openalex.org/W3101588560","https://openalex.org/W3101707147","https://openalex.org/W3105879597","https://openalex.org/W3106252282","https://openalex.org/W3122507327","https://openalex.org/W3166827814","https://openalex.org/W3178807794","https://openalex.org/W4250050336","https://openalex.org/W4288080214","https://openalex.org/W4288083766","https://openalex.org/W4297971002"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Sequential":[0,99],"Recommendation":[1,100],"aims":[2],"to":[3,80,134,141,145],"recommend":[4],"items":[5],"that":[6],"a":[7,57,77,92,119,182],"target":[8],"user":[9,41,83,136],"will":[10],"interact":[11],"with":[12,181],"in":[13,49,64],"the":[14,19,34,40,45,50,53,61,65,68,105,110,115,143,176],"near":[15],"future":[16],"based":[17,161],"on":[18,39,162,168],"historically":[20],"interacted":[21],"items.":[22],"While":[23],"modeling":[24],"temporal":[25,148,154,163],"dynamics":[26,62,111],"is":[27],"crucial":[28],"for":[29,98,108,124],"sequential":[30,46,178],"recommendation,":[31],"most":[32],"of":[33],"existing":[35,48],"studies":[36,59],"concentrate":[37],"solely":[38],"side":[42],"while":[43],"overlooking":[44],"patterns":[47],"counterpart,":[51],"i.e.,":[52],"item":[54,85,138],"side.":[55],"Although":[56],"few":[58],"investigate":[60],"involved":[63],"dual":[66],"sides,":[67,114],"complex":[69],"user-item":[70,106,121],"interactions":[71,107],"are":[72],"not":[73],"fully":[74],"exploited":[75],"from":[76,112],"global":[78,120],"perspective":[79],"derive":[81],"dynamic":[82],"and":[84,128,137],"representations.":[86,139],"In":[87],"this":[88],"paper,":[89],"we":[90,150],"devise":[91],"novel":[93],"Dynamic":[94],"Representation":[95],"Learning":[96],"model":[97,104,117,144],"(DRL-SRe).":[101],"To":[102],"better":[103],"characterizing":[109],"both":[113],"proposed":[116],"builds":[118],"interaction":[122],"graph":[123,131],"each":[125],"time":[126,159],"slice":[127],"exploit":[129],"time-sliced":[130],"neural":[132],"networks":[133],"learn":[135],"Moreover,":[140],"enable":[142],"capture":[146],"fine-grained":[147],"information,":[149],"propose":[151],"an":[152],"auxiliary":[153],"prediction":[155],"task":[156],"over":[157],"consecutive":[158],"slices":[160],"point":[164],"process.":[165],"Comprehensive":[166],"experiments":[167],"three":[169],"public":[170],"real-world":[171],"datasets":[172],"demonstrate":[173],"DRL-SRe":[174],"outperforms":[175],"state-of-the-art":[177],"recommendation":[179],"models":[180],"large":[183],"margin.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}