{"id":"https://openalex.org/W3034246682","doi":"https://doi.org/10.1145/3397271.3401201","title":"Metadata Matters in User Engagement Prediction","display_name":"Metadata Matters in User Engagement Prediction","publication_year":2020,"publication_date":"2020-07-25","ids":{"openalex":"https://openalex.org/W3034246682","doi":"https://doi.org/10.1145/3397271.3401201","mag":"3034246682"},"language":"en","primary_location":{"id":"doi:10.1145/3397271.3401201","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5100441911","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0002-1180-3891"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiang Chen","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003506066","display_name":"Saayan Mitra","orcid":"https://orcid.org/0000-0002-4048-2142"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saayan Mitra","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022934605","display_name":"Viswanathan Swaminathan","orcid":"https://orcid.org/0000-0002-1357-1502"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viswanathan Swaminathan","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100441911"],"corresponding_institution_ids":["https://openalex.org/I1306409833"],"apc_list":null,"apc_paid":null,"fwci":0.8007,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.79695175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1529","last_page":"1532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9887999892234802,"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/metadata","display_name":"Metadata","score":0.9430063962936401},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.841045618057251},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6579117774963379},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6283447742462158},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5028290152549744},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4734732210636139},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.4626098573207855},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4246135354042053},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41149258613586426},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.40067562460899353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3375367522239685}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.9430063962936401},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.841045618057251},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6579117774963379},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6283447742462158},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5028290152549744},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4734732210636139},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.4626098573207855},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4246135354042053},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41149258613586426},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.40067562460899353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3375367522239685},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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":1,"locations":[{"id":"doi:10.1145/3397271.3401201","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2030602513","https://openalex.org/W2074694452","https://openalex.org/W2074796565","https://openalex.org/W2076618162","https://openalex.org/W2295739661","https://openalex.org/W2475334473","https://openalex.org/W2509235963","https://openalex.org/W2523437372","https://openalex.org/W2548570154","https://openalex.org/W2618087227","https://openalex.org/W2723293840","https://openalex.org/W2946044191","https://openalex.org/W2951001079","https://openalex.org/W3104789011"],"related_works":["https://openalex.org/W2058118494","https://openalex.org/W2392768766","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W3164948662","https://openalex.org/W3105157121","https://openalex.org/W3104067163","https://openalex.org/W3153597579","https://openalex.org/W4382049132","https://openalex.org/W3159661535"],"abstract_inverted_index":{"Predicting":[0],"user":[1,24,50,68,90,134],"engagement":[2,91],"(e.g.,":[3,65],"click-through":[4],"rate,":[5],"conversion":[6],"rate)":[7],"on":[8,40,57,165],"the":[9,18,22,42,49,59,63,77,82,86,89,103,117,124,138,141,147,150,159,171,179],"display":[10],"ads":[11],"plays":[12],"a":[13,97,127,166],"critical":[14],"role":[15],"in":[16,25,88,112],"delivering":[17],"right":[19,23],"ad":[20,60,125],"to":[21,33,47,75,132,176],"online":[26],"advertising.":[27],"Existing":[28],"techniques":[29],"spanning":[30],"Logistic":[31],"Regression":[32],"Factorization":[34],"Machines":[35],"and":[36,116,156],"their":[37],"derivatives,":[38],"focus":[39],"modeling":[41],"interactions":[43],"among":[44],"handcrafted":[45],"features":[46],"predict":[48,133],"engagement.":[51,135],"Little":[52],"attention":[53],"has":[54],"been":[55,109],"paid":[56],"how":[58],"fits":[61],"with":[62],"context":[64,105],"hosted":[66],"webpage,":[67],"demographics).":[69],"In":[70,94],"this":[71],"paper,":[72],"we":[73,100,145],"propose":[74],"include":[76],"metadata":[78,118,143,160,172],"feature,":[79,119,144],"which":[80,107,120],"captures":[81],"visual":[83],"appearance":[84],"of":[85,140,149],"ad,":[87],"prediction":[92,114,153,180],"task.":[93],"particular,":[95],"given":[96],"data":[98],"sample,":[99],"combine":[101],"both":[102],"basic":[104],"features,":[106],"have":[108],"widely":[110,151],"used":[111,152],"existing":[113],"models,":[115],"is":[121,174],"extracted":[122],"from":[123],"using":[126],"state-of-the-art":[128],"deep":[129],"learning":[130],"framework,":[131],"To":[136],"demonstrate":[137,169],"effectiveness":[139],"proposed":[142],"compare":[146],"performance":[148],"models":[154],"before":[155],"after":[157],"integrating":[158],"feature.":[161],"Our":[162],"experimental":[163],"results":[164],"real-world":[167],"dataset":[168],"that":[170],"feature":[173],"able":[175],"further":[177],"improve":[178],"performance.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
