{"id":"https://openalex.org/W4412376920","doi":"https://doi.org/10.1145/3726302.3730177","title":"Deep Multiple Quantization Network on Long Behavior Sequence for Click-Through Rate Prediction","display_name":"Deep Multiple Quantization Network on Long Behavior Sequence for Click-Through Rate Prediction","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376920","doi":"https://doi.org/10.1145/3726302.3730177"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730177","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730177","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730177","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730177","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhuoxing Wei","orcid":"https://orcid.org/0009-0005-7302-063X"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuoxing Wei","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0005-7302-063X","affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qi Liu","orcid":"https://orcid.org/0009-0005-0353-7211"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":["University of Science and Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0005-0353-7211","affiliations":[{"raw_affiliation_string":"University of Science and Technology, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":null,"display_name":"Qingchen Xie","orcid":"https://orcid.org/0009-0008-0464-2672"},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingchen Xie","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-0464-2672","affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210087373"],"apc_list":null,"apc_paid":null,"fwci":5.4855,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.94633031,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3090","last_page":"3094"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/quantization","display_name":"Quantization (signal processing)","score":0.6980756521224976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6303718686103821},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5679452419281006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45307254791259766},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3652884066104889},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33037203550338745}],"concepts":[{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6980756521224976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6303718686103821},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5679452419281006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45307254791259766},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3652884066104889},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33037203550338745},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3726302.3730177","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730177","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730177","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2508.20865","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.20865","pdf_url":"https://arxiv.org/pdf/2508.20865","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"doi:10.1145/3726302.3730177","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730177","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730177","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376920.pdf","grobid_xml":"https://content.openalex.org/works/W4412376920.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2077815765","https://openalex.org/W2124509324","https://openalex.org/W2723293840","https://openalex.org/W2945772520","https://openalex.org/W2962745591","https://openalex.org/W3012754345","https://openalex.org/W3093519337","https://openalex.org/W3106252282","https://openalex.org/W4213069590","https://openalex.org/W4306317673"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W4409439182","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2052122378","https://openalex.org/W2544423928","https://openalex.org/W2062023542"],"abstract_inverted_index":{"In":[0],"Click-Through":[1],"Rate":[2],"(CTR)":[3],"prediction,":[4],"the":[5,10,25,29,61,69,73,86,90,104,109,136,145,153,163,181],"long":[6,12,75,98,105,113],"behavior":[7,76,99,106,114],"sequence,":[8],"comprising":[9],"user's":[11,26],"period":[13],"of":[14,45,112,138,162,185],"historical":[15],"interactions":[16],"with":[17],"items":[18,47,71],"has":[19],"a":[20,39,81],"vital":[21],"influence":[22],"on":[23,124,174],"assessing":[24],"interest":[27,51,154],"in":[28,63,190],"candidate":[30,146],"item.":[31],"Existing":[32],"approaches":[33],"strike":[34],"efficiency":[35,184],"and":[36,48,72,147,177,183,201],"effectiveness":[37,182],"through":[38,54,102],"two-stage":[40],"paradigm:":[41],"first":[42],"retrieving":[43],"hundreds":[44],"candidate-related":[46],"then":[49],"extracting":[50],"intensity":[52],"vector":[53],"target":[55,64],"attention.":[56],"However,":[57],"we":[58,88],"argue":[59],"that":[60,195],"discrepancy":[62],"attention's":[65],"relevance":[66],"distribution":[67],"between":[68,144],"retrieved":[70],"full":[74],"sequence":[77,100,115],"inevitably":[78],"leads":[79],"to":[80,96,134],"performance":[82],"decline.":[83],"To":[84,156],"alleviate":[85],"discrepancy,":[87],"propose":[89],"Deep":[91],"Multiple":[92],"Quantization":[93],"Network":[94],"(DMQN)":[95],"process":[97],"end-to-end":[101],"compressing":[103],"sequence.":[107],"Firstly,":[108],"entire":[110],"spectrum":[111],"will":[116,151],"be":[117],"quantized":[118],"into":[119],"multiple":[120,125,148],"codeword":[121,140,149,164],"sequences":[122,150,165],"based":[123],"independent":[126],"codebooks.":[127],"Hierarchical":[128],"Sequential":[129],"Transduction":[130],"Unit":[131],"is":[132],"incorporated":[133],"facilitate":[135],"interaction":[137],"reduced":[139],"sequences.":[141],"Then,":[142],"attention":[143],"output":[152],"vector.":[155],"enable":[157],"online":[158],"serving,":[159],"intermediate":[160],"representations":[161],"are":[166],"cached,":[167],"significantly":[168],"reducing":[169],"latency.":[170],"Our":[171],"extensive":[172],"experiments":[173],"both":[175],"industrial":[176],"public":[178],"datasets":[179],"confirm":[180],"DMQN.":[186],"The":[187],"A/B":[188],"test":[189],"our":[191],"advertising":[192],"system":[193],"shows":[194],"DMQN":[196],"improves":[197],"CTR":[198],"by":[199,203],"3.5%":[200],"RPM":[202],"2.0%.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
