{"id":"https://openalex.org/W3080510735","doi":"https://doi.org/10.1145/3394486.3403297","title":"Combo-Attention Network for Baidu Video Advertising","display_name":"Combo-Attention Network for Baidu Video Advertising","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3080510735","doi":"https://doi.org/10.1145/3394486.3403297","mag":"3080510735"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403297","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","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/A5018887598","display_name":"Tan Yu","orcid":"https://orcid.org/0000-0001-6071-0395"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan Yu","raw_affiliation_strings":["Baidu Research, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research, Seattle, WA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747784","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0001-5077-4782"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421473","display_name":"Yi Li","orcid":"https://orcid.org/0000-0002-2856-7290"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Li","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaodong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Chen","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103150619","display_name":"Mingming Sun","orcid":"https://orcid.org/0000-0002-6199-4905"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingming Sun","raw_affiliation_strings":["Baidu Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100741315","display_name":"Ping Li","orcid":"https://orcid.org/0000-0002-8515-7773"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Li","raw_affiliation_strings":["Baidu Research, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Research, Seattle, WA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8388,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.9240609,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2474","last_page":"2482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9983000159263611,"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":0.8335704207420349},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6402772068977356},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5869619846343994},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5028092861175537},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.48783448338508606},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.48509395122528076},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.4839525520801544},{"id":"https://openalex.org/keywords/online-advertising","display_name":"Online advertising","score":0.4632512331008911},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.46261388063430786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3451218903064728},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3127763867378235},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.1693563163280487},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.10644650459289551}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8335704207420349},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6402772068977356},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5869619846343994},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5028092861175537},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48783448338508606},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.48509395122528076},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.4839525520801544},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.4632512331008911},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.46261388063430786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3451218903064728},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3127763867378235},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.1693563163280487},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10644650459289551},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403297","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W877909479","https://openalex.org/W1522734439","https://openalex.org/W1573040851","https://openalex.org/W1897761818","https://openalex.org/W1916445035","https://openalex.org/W2064987260","https://openalex.org/W2156037541","https://openalex.org/W2194775991","https://openalex.org/W2277195237","https://openalex.org/W2490414731","https://openalex.org/W2508429489","https://openalex.org/W2540404261","https://openalex.org/W2558687840","https://openalex.org/W2560674852","https://openalex.org/W2560835477","https://openalex.org/W2565656701","https://openalex.org/W2727849499","https://openalex.org/W2806331055","https://openalex.org/W2808399042","https://openalex.org/W2950960796","https://openalex.org/W2952186347","https://openalex.org/W2962964995","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963499204","https://openalex.org/W2963524571","https://openalex.org/W2964265128","https://openalex.org/W2964308564","https://openalex.org/W2966683369","https://openalex.org/W2970547183","https://openalex.org/W2970608575","https://openalex.org/W2978329087","https://openalex.org/W2981851019","https://openalex.org/W2984020950","https://openalex.org/W2989322838","https://openalex.org/W3010969086","https://openalex.org/W3028864969","https://openalex.org/W3034709327","https://openalex.org/W4310895557"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2348524959","https://openalex.org/W2518037665","https://openalex.org/W2368049389","https://openalex.org/W1496222301","https://openalex.org/W2384861574","https://openalex.org/W3207760230","https://openalex.org/W2952704802","https://openalex.org/W2092674857","https://openalex.org/W4236168950"],"abstract_inverted_index":{"With":[0],"the":[1,7,10,17,56,63,96,105,114,117,149,176,190,204,213,216,242,249],"progress":[2],"of":[3,9,72,160,171,215,244],"communication":[4],"technology":[5],"and":[6,28,128,141,164,174,208,267],"popularity":[8],"smart":[11],"phone,":[12],"videos":[13,21,103],"grow":[14],"to":[15,45,54,95,113,201],"be":[16],"largest":[18],"medium.":[19],"Since":[20],"can":[22,35],"grab":[23],"a":[24,30,82,109,137,155,158,166,169,180,222,237,260,268],"customer's":[25],"attention":[26],"quickly":[27],"leave":[29],"big":[31],"impression,":[32],"video":[33,52,87,92,146,156,255],"ads":[34,53,93],"gain":[36],"more":[37,47,121],"trust":[38],"than":[39,123],"traditional":[40],"ads.":[41],"Thus":[42],"advertisers":[43],"start":[44],"pour":[46],"resources":[48],"into":[49],"making":[50],"creative":[51],"built":[55,188,221],"connections":[57],"with":[58],"potential":[59],"customers.":[60],"Baidu,":[61],"as":[62,157,168,179,234,236],"leading":[64],"search":[65,73,119,127,178],"engine":[66],"company":[67],"in":[68,85,144,252,263,271],"China,":[69],"receives":[70],"billions":[71],"queries":[74],"per":[75],"day.":[76],"In":[77,148],"this":[78,133],"paper,":[79],"we":[80,135,153,220,258],"introduce":[81],"technique":[83],"used":[84],"Baidu":[86,145],"advertising":[88,256],"for":[89],"feeding":[90],"relevant":[91,102],"according":[94],"user's":[97],"query.":[98],"Note":[99],"that,":[100],"retrieving":[101],"using":[104],"text":[106],"query":[107],"is":[108,120,187],"cross-modal":[110,196],"problem.":[111,183],"Due":[112],"modal":[115],"gap,":[116],"text-to-video":[118],"challenging":[122],"well":[124,235],"exploited":[125],"text-to-text":[126],"image-to-image":[129],"search.":[130],"To":[131,211],"tackle":[132],"challenge,":[134],"propose":[136],"Combo-Attention":[138],"Network":[139],"(CAN)":[140],"launch":[142],"it":[143],"advertising.":[147],"proposed":[150,185,191,217,250],"CAN":[151,186,218,251],"model,":[152],"represent":[154,165],"set":[159,170],"bounding":[161,209],"boxes":[162],"features":[163],"sentence":[167],"words":[172,207],"features,":[173],"formulate":[175],"sentence-to-video":[177],"set-to-set":[181],"matching":[182],"The":[184,229],"upon":[189],"combo-attention":[192],"module,":[193],"which":[194],"exploits":[195],"attentions":[197,200],"besides":[198],"self":[199],"effectively":[202],"capture":[203],"relevance":[205],"between":[206],"boxes.":[210],"testify":[212],"effectiveness":[214,243],"offline,":[219],"Daily700K":[223,233],"dataset":[224],"collected":[225],"from":[226],"HaoKan":[227],"APP.":[228],"systematic":[230],"experiments":[231],"on":[232],"public":[238],"dataset,":[239],"VATEX,":[240],"demonstrate":[241],"our":[245],"CAN.":[246],"After":[247],"launching":[248],"Baidu's":[253],"dynamic":[254],"(DVA),":[257],"achieve":[259],"$5.47%$":[261],"increase":[262,270],"Conversion":[264],"Rate":[265],"(CVR)":[266],"$11.69%$":[269],"advertisement":[272],"impression":[273],"rate.":[274]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":14}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
