{"id":"https://openalex.org/W3034260007","doi":"https://doi.org/10.24963/ijcai.2020/487","title":"An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration","display_name":"An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3034260007","doi":"https://doi.org/10.24963/ijcai.2020/487","mag":"3034260007"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/487","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/487","pdf_url":"https://www.ijcai.org/proceedings/2020/0487.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0487.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101039314","display_name":"Yumin Su","orcid":"https://orcid.org/0009-0006-0295-4141"},"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":"Yumin Su","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425247","display_name":"Liang Zhang","orcid":"https://orcid.org/0000-0002-8514-5123"},"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":"Liang Zhang","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048783161","display_name":"Quanyu Dai","orcid":"https://orcid.org/0000-0001-7578-2738"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Quanyu Dai","raw_affiliation_strings":["The Hong Kong Polytechnic University","The Hong Kong Polytechnic University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"The Hong Kong Polytechnic University,","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101550053","display_name":"Bo Zhang","orcid":"https://orcid.org/0000-0002-7226-1088"},"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":"Bo Zhang","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077266611","display_name":"Jinyao Yan","orcid":"https://orcid.org/0000-0003-4153-313X"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyao Yan","raw_affiliation_strings":["Communication University of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication University of China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411794","display_name":"Dan Wang","orcid":"https://orcid.org/0000-0002-0921-2726"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Dan Wang","raw_affiliation_strings":["The Hong Kong Polytechnic University","The Hong Kong Polytechnic University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"The Hong Kong Polytechnic University,","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089195488","display_name":"Yongjun Bao","orcid":"https://orcid.org/0000-0002-4957-9813"},"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":"Yongjun Bao","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010637653","display_name":"Sulong Xu","orcid":"https://orcid.org/0009-0001-1610-6008"},"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":"Sulong Xu","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021662942","display_name":"Yang He","orcid":"https://orcid.org/0000-0002-2257-6073"},"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":"Yang He","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103185227","display_name":"Weipeng Yan","orcid":"https://orcid.org/0000-0001-5112-2655"},"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":"Weipeng Yan","raw_affiliation_strings":["JD.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3418,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.93522564,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3522","last_page":"3528"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9993000030517578,"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":0.9993000030517578,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.8391491174697876},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.7383745908737183},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5312081575393677},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4878566265106201},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45166850090026855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43261927366256714},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3874160051345825},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11415606737136841}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8391491174697876},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.7383745908737183},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5312081575393677},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4878566265106201},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45166850090026855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43261927366256714},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3874160051345825},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11415606737136841}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2020/487","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/487","pdf_url":"https://www.ijcai.org/proceedings/2020/0487.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-168012","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-168012","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"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":"Conference paper"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/487","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/487","pdf_url":"https://www.ijcai.org/proceedings/2020/0487.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3034260007.pdf","grobid_xml":"https://content.openalex.org/works/W3034260007.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1970210633","https://openalex.org/W2012905273","https://openalex.org/W2021866613","https://openalex.org/W2103020160","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2158698691","https://openalex.org/W2171461858","https://openalex.org/W2511146301","https://openalex.org/W2586345506","https://openalex.org/W2723293840","https://openalex.org/W2753415251","https://openalex.org/W2768307941","https://openalex.org/W2785978487","https://openalex.org/W2799125281","https://openalex.org/W2953384591","https://openalex.org/W2962989965","https://openalex.org/W2964267165","https://openalex.org/W2964308564","https://openalex.org/W4295725475"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W4380075502","https://openalex.org/W2955214695","https://openalex.org/W2994695002","https://openalex.org/W3155121005","https://openalex.org/W3190524507","https://openalex.org/W4296605900"],"abstract_inverted_index":{"Conversion":[0],"rate":[1],"(CVR)":[2],"prediction":[3],"is":[4,27],"becoming":[5],"increasingly":[6],"important":[7],"in":[8,89,132],"the":[9,22,33,37,40,76,82,99,106,113,118,127,135,146,149],"multi-billion":[10],"dollar":[11],"online":[12],"display":[13],"advertising":[14],"industry.":[15],"It":[16],"has":[17],"two":[18,77],"major":[19],"challenges:":[20],"firstly,":[21],"scarce":[23,59],"user":[24,142],"history":[25],"data":[26,130,144],"very":[28,45],"complicated":[29],"and":[30,39,60,92],"non-linear;":[31],"secondly,":[32],"time":[34],"delay":[35,119],"between":[36],"clicks":[38],"corresponding":[41],"conversions":[42],"can":[43],"be":[44],"large,":[46],"e.g.,":[47],"ranging":[48],"from":[49,57,85,105],"seconds":[50],"to":[51,74,87,97,111],"weeks.":[52],"Existing":[53],"models":[54,91],"usually":[55],"suffer":[56],"such":[58],"delayed":[61],"conversion":[62,90],"behaviors.":[63],"In":[64],"this":[65],"paper,":[66],"we":[67,80,116],"propose":[68,93],"a":[69],"novel":[70],"deep":[71],"learning":[72,122],"framework":[73],"tackle":[75],"challenges.":[78],"Specifically,":[79],"extract":[81],"pre-trained":[83],"embedding":[84],"impressions/clicks":[86],"assist":[88],"an":[94],"inner/self-attention":[95],"mechanism":[96],"capture":[98],"fine-grained":[100],"personalized":[101],"product":[102],"purchase":[103],"interests":[104],"sequential":[107],"click":[108],"data.":[109],"Besides,":[110],"overcome":[112],"time-delay":[114],"issue,":[115],"calibrate":[117],"model":[120],"by":[121],"dynamic":[123],"hazard":[124],"function":[125],"with":[126,134,140],"abundant":[128],"post-click":[129],"more":[131],"line":[133],"real":[136],"distribution.":[137],"Empirical":[138],"experiments":[139],"real-world":[141],"behavior":[143],"prove":[145],"effectiveness":[147],"of":[148],"proposed":[150],"method.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}