{"id":"https://openalex.org/W2783666221","doi":"https://doi.org/10.1145/3219819.3219826","title":"Learning Tree-based Deep Model for Recommender Systems","display_name":"Learning Tree-based Deep Model for Recommender Systems","publication_year":2018,"publication_date":"2018-07-19","ids":{"openalex":"https://openalex.org/W2783666221","doi":"https://doi.org/10.1145/3219819.3219826","mag":"2783666221"},"language":"en","primary_location":{"id":"doi:10.1145/3219819.3219826","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3219819.3219826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1801.02294","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063667378","display_name":"Zhu Han","orcid":"https://orcid.org/0000-0002-6606-5822"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Han Zhu","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100330993","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0001-5471-1236"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053036893","display_name":"Pengye Zhang","orcid":"https://orcid.org/0009-0008-1776-2876"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengye Zhang","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089711319","display_name":"Guozheng Li","orcid":"https://orcid.org/0000-0001-5568-0347"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guozheng Li","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049875848","display_name":"Jie He","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie He","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062225796","display_name":"Han Li","orcid":"https://orcid.org/0000-0003-4638-9907"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Li","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062939922","display_name":"Kun Gai","orcid":"https://orcid.org/0000-0002-3636-3618"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Gai","raw_affiliation_strings":["Alibaba Group, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Beijing, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5063667378"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":50.1729,"has_fulltext":false,"cited_by_count":289,"citation_normalized_percentile":{"value":0.99813752,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1079","last_page":"1088"},"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/T10028","display_name":"Topic Modeling","score":0.9947999715805054,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9919000267982483,"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":0.8790996074676514},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8124070167541504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5987086296081543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5439115166664124},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5170438885688782},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.47589218616485596},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.45867544412612915},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4376181364059448},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40103477239608765},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3910055160522461}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8790996074676514},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8124070167541504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5987086296081543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5439115166664124},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5170438885688782},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.47589218616485596},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.45867544412612915},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4376181364059448},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40103477239608765},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3910055160522461},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3219819.3219826","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3219819.3219826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1801.02294","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.02294","pdf_url":"https://arxiv.org/pdf/1801.02294","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"pmh:oai:arXiv.org:1801.02294","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.02294","pdf_url":"https://arxiv.org/pdf/1801.02294","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W36903255","https://openalex.org/W1498860622","https://openalex.org/W1579592807","https://openalex.org/W1834987204","https://openalex.org/W1836465849","https://openalex.org/W1921523184","https://openalex.org/W1965355809","https://openalex.org/W2036907820","https://openalex.org/W2038721957","https://openalex.org/W2042281163","https://openalex.org/W2054141820","https://openalex.org/W2068074736","https://openalex.org/W2100664567","https://openalex.org/W2106854428","https://openalex.org/W2137245235","https://openalex.org/W2140310134","https://openalex.org/W2150385485","https://openalex.org/W2155144632","https://openalex.org/W2159094788","https://openalex.org/W2165874743","https://openalex.org/W2219888463","https://openalex.org/W2295739661","https://openalex.org/W2362855512","https://openalex.org/W2475334473","https://openalex.org/W2508504774","https://openalex.org/W2512971201","https://openalex.org/W2517672267","https://openalex.org/W2548570154","https://openalex.org/W2593864460","https://openalex.org/W2604202871","https://openalex.org/W2605350416","https://openalex.org/W2606642831","https://openalex.org/W2723293840","https://openalex.org/W2769293999","https://openalex.org/W2788125442","https://openalex.org/W2949117887","https://openalex.org/W2950133940","https://openalex.org/W2950274046","https://openalex.org/W2950961224","https://openalex.org/W2951066642","https://openalex.org/W2998702515","https://openalex.org/W3004786981","https://openalex.org/W3101681922","https://openalex.org/W3194416009","https://openalex.org/W4285719527","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W3208304128","https://openalex.org/W2979433843"],"abstract_inverted_index":{"Model-based":[0],"methods":[1],"for":[2,21,169],"recommender":[3,117],"systems":[4,13,118],"have":[5],"been":[6],"studied":[7],"extensively":[8],"in":[9,162,218,231],"recent":[10],"years.":[11],"In":[12,103],"with":[14,119,137,187,200],"large":[15,120],"corpus,":[16],"however,":[17],"the":[18,22,41,59,100,109,177,207,225,228],"calculation":[19,42,101],"cost":[20],"learnt":[23,183],"model":[24,55],"to":[25,50,69,81,116,150,156],"predict":[26,151],"all":[27],"user-item":[28,56],"preferences":[29],"is":[30,149],"tremendous,":[31],"which":[32,128],"makes":[33],"full":[34],"corpus":[35,134],"retrieval":[36],"extremely":[37],"difficult.":[38],"To":[39],"overcome":[40],"barriers,":[43],"models":[44,115,140],"such":[45,141],"as":[46,58,142],"matrix":[47],"factorization":[48],"resort":[49],"inner":[51,60],"product":[52,61],"form":[53],"(i.e.,":[54],"preference":[57],"of":[62,99,111,227],"user,":[63],"item":[64,90],"latent":[65],"factors)":[66],"and":[67,89,166,191,196],"indexes":[68],"facilitate":[70,193],"efficient":[71],"approximate":[72],"k-nearest":[73],"neighbor":[74],"searches.":[75],"However,":[76],"it":[77],"still":[78],"remains":[79],"challenging":[80],"incorporate":[82],"more":[83,138],"expressive":[84,139],"interaction":[85],"forms":[86],"between":[87],"user":[88,152],"features,":[91],"e.g.,":[92],"interactions":[93],"through":[94],"deep":[95,143],"neural":[96,144],"networks,":[97],"because":[98],"cost.":[102],"this":[104],"paper,":[105],"we":[106],"focus":[107],"on":[108],"problem":[110],"introducing":[112],"arbitrary":[113],"advanced":[114],"corpus.":[121],"We":[122,173],"propose":[123],"a":[124,163],"novel":[125],"tree-based":[126],"method":[127,209,230],"can":[129,180],"provide":[130],"logarithmic":[131],"complexity":[132],"w.r.t.":[133],"size":[135],"even":[136],"networks.":[145],"Our":[146],"main":[147],"idea":[148],"interests":[153],"from":[154],"coarse":[155],"fine":[157],"by":[158],"traversing":[159],"tree":[160,178],"nodes":[161],"top-down":[164],"fashion":[165],"making":[167],"decisions":[168],"each":[170],"user-node":[171],"pair.":[172],"also":[174,223],"show":[175,205],"that":[176,206],"structure":[179],"be":[181],"jointly":[182],"towards":[184],"better":[185],"compatibility":[186],"users'":[188],"interest":[189],"distribution":[190],"hence":[192],"both":[194],"training":[195],"prediction.":[197],"Experimental":[198],"evaluations":[199],"two":[201],"large-scale":[202],"real-world":[203],"datasets":[204],"proposed":[208,229],"significantly":[210],"outperforms":[211],"traditional":[212],"methods.":[213],"Online":[214],"A/B":[215],"test":[216],"results":[217],"Taobao":[219],"display":[220],"advertising":[221],"platform":[222],"demonstrate":[224],"effectiveness":[226],"production":[232],"environments.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":39},{"year":2023,"cited_by_count":50},{"year":2022,"cited_by_count":43},{"year":2021,"cited_by_count":50},{"year":2020,"cited_by_count":46},{"year":2019,"cited_by_count":24},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}