{"id":"https://openalex.org/W2964809821","doi":"https://doi.org/10.24963/ijcai.2019/190","title":"Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation","display_name":"Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2964809821","doi":"https://doi.org/10.24963/ijcai.2019/190","mag":"2964809821"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/190","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/190","pdf_url":"https://www.ijcai.org/proceedings/2019/0190.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0190.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007061198","display_name":"Guibing Guo","orcid":"https://orcid.org/0000-0002-1709-5056"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guibing Guo","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060990321","display_name":"Shichang Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shichang Ouyang","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727205","display_name":"Xiaodong He","orcid":"https://orcid.org/0000-0002-9463-9168"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong He","raw_affiliation_strings":["JD AI Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081665927","display_name":"Fajie Yuan","orcid":"https://orcid.org/0000-0001-8452-9929"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fajie Yuan","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100370790","display_name":"Xiaohua Liu","orcid":"https://orcid.org/0000-0003-0384-5431"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Liu","raw_affiliation_strings":["JD AI Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD AI Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081665927"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1373","last_page":"1379"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9911999702453613,"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":0.8379195928573608},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7376578450202942},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6518744230270386},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6470543146133423},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.6266981959342957},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5164730548858643},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4978663921356201},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.48558229207992554},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4569225311279297},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43340760469436646},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.43002113699913025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4200893044471741},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3543318212032318},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.12225183844566345},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08221879601478577}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8379195928573608},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7376578450202942},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6518744230270386},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6470543146133423},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.6266981959342957},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5164730548858643},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4978663921356201},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.48558229207992554},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4569225311279297},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43340760469436646},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.43002113699913025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4200893044471741},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3543318212032318},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.12225183844566345},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08221879601478577},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/190","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/190","pdf_url":"https://www.ijcai.org/proceedings/2019/0190.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/190","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/190","pdf_url":"https://www.ijcai.org/proceedings/2019/0190.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4591949316","display_name":null,"funder_award_id":"N181705007","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5219054260","display_name":"\u8282\u70b9\u51b3\u7b56\u8ba4\u77e5\u7684\u5728\u7ebf\u793e\u4ea4\u4fe1\u606f\u6269\u6563\u52a8\u529b\u4e0e\u6709\u5e8f\u4f20\u64ad\u673a\u5236\u7814\u7a76","funder_award_id":"61772125","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6469584554","display_name":null,"funder_award_id":"61702090","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6732846715","display_name":null,"funder_award_id":"61772125","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8803915367","display_name":null,"funder_award_id":"61702084","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8828627166","display_name":null,"funder_award_id":"61702084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G983970540","display_name":null,"funder_award_id":"61702090","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964809821.pdf","grobid_xml":"https://content.openalex.org/works/W2964809821.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2027731328","https://openalex.org/W2080320419","https://openalex.org/W2138204974","https://openalex.org/W2140310134","https://openalex.org/W2157973827","https://openalex.org/W2171279286","https://openalex.org/W2183212076","https://openalex.org/W2605350416","https://openalex.org/W2783272285","https://openalex.org/W2783944588","https://openalex.org/W2808246249","https://openalex.org/W2808490894","https://openalex.org/W2902040508","https://openalex.org/W2964296635","https://openalex.org/W3098649723","https://openalex.org/W4299286960"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W3005627584","https://openalex.org/W4303493643"],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1],"systems":[2],"have":[3],"become":[4],"a":[5,46,65,68,76,110,140,171,174,187,199],"research":[6],"hotpot":[7],"recently":[8],"to":[9,55,115,145],"suggest":[10],"users":[11,57],"with":[12,53,139,206],"the":[13,85,122,128,179,207],"next":[14],"item":[15,33,48,72,118,130,181],"of":[16,31,64,87,124,189,209,215],"interest":[17],"(to":[18],"interact":[19],"with).":[20],"However,":[21],"existing":[22],"approaches":[23],"suffer":[24],"from":[25,225],"two":[26,100],"limitations:":[27],"(1)":[28],"The":[29,62,218],"representation":[30,119,148],"an":[32,71],"is":[34,73,168],"relatively":[35],"static":[36],"and":[37,58,160,195,211,220],"fixed":[38],"for":[39,67,104,163,183],"all":[40],"users.":[41],"We":[42,185],"argue":[43],"that":[44,132,197],"even":[45,198],"same":[47,129],"should":[49],"be":[50,158,203,223],"represented":[51],"distinctively":[52],"respect":[54],"different":[56],"time":[59,133],"steps.":[60],"(2)":[61],"generation":[63],"prediction":[66,167],"user":[69,89,147],"over":[70,173],"computed":[74],"in":[75,95,213],"single":[77],"scale":[78],"(e.g.,":[79],"by":[80,120,170],"their":[81],"inner":[82],"product),":[83],"ignoring":[84],"nature":[86],"multi-scale":[88],"preferences.":[90],"To":[91],"resolve":[92],"these":[93],"issues,":[94],"this":[96],"paper":[97],"we":[98,108,136],"propose":[99],"enhancing":[101],"building":[102],"blocks":[103],"sequential":[105],"recommendation.":[106],"Specifically,":[107],"devise":[109],"Dynamic":[111],"Item":[112],"Block":[113,143],"(DIB)":[114],"learn":[116],"dynamic":[117],"aggregating":[121],"embeddings":[123],"those":[125],"who":[126],"rated":[127],"before":[131],"step.":[134],"Then,":[135],"come":[137],"up":[138],"Prediction":[141],"Enhancing":[142],"(PEB)":[144],"project":[146],"into":[149],"multiple":[150],"scales,":[151],"based":[152],"on":[153,191],"which":[154],"many":[155],"predictions":[156],"can":[157,202,222],"made":[159],"attentively":[161],"aggregated":[162],"enhanced":[164,205],"learning.":[165],"Each":[166],"generated":[169],"softmax":[172],"sampled":[175],"itemset":[176],"rather":[177],"than":[178],"whole":[180],"space":[182],"efficiency.":[184],"conduct":[186],"series":[188],"experiments":[190],"four":[192],"real":[193],"datasets,":[194],"show":[196],"basic":[200],"model":[201],"greatly":[204],"involvement":[208],"DIB":[210],"PEB":[212],"terms":[214],"ranking":[216],"accuracy.":[217],"code":[219],"datasets":[221],"obtained":[224],"https://github.com/ouououououou/DIB-PEB-Sequential-RS":[226]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
