{"id":"https://openalex.org/W2963908715","doi":"https://doi.org/10.1145/3126686.3126745","title":"Tag Prediction at Flickr","display_name":"Tag Prediction at Flickr","publication_year":2017,"publication_date":"2017-10-23","ids":{"openalex":"https://openalex.org/W2963908715","doi":"https://doi.org/10.1145/3126686.3126745","mag":"2963908715"},"language":"en","primary_location":{"id":"doi:10.1145/3126686.3126745","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3126686.3126745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the on Thematic Workshops of ACM Multimedia 2017","raw_type":"proceedings-article"},"type":"conference-paper","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/A5050639290","display_name":"Kofi Boakye","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kofi Boakye","raw_affiliation_strings":["Yahoo Research, San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research, San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002007869","display_name":"Sachin Farfade","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sachin Farfade","raw_affiliation_strings":["Yahoo Research, Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035839484","display_name":"Hamid Izadinia","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamid Izadinia","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042126127","display_name":"Yannis Kalantidis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yannis Kalantidis","raw_affiliation_strings":["Facebook, Menlo Park, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, CA, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076616566","display_name":"Pierre Garrigues","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pierre Garrigues","raw_affiliation_strings":["Yahoo Research, San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Research, San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210134091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"376","last_page":"384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994999766349792,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9979000091552734,"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":0.8373558521270752},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.8353425860404968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6299858093261719},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5841129422187805},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5729615092277527},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5097550749778748},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5059108138084412},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.46266794204711914},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46088907122612},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.46067413687705994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44572460651397705},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42312347888946533},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41881299018859863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38179337978363037},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.19739821553230286}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8373558521270752},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.8353425860404968},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6299858093261719},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5841129422187805},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5729615092277527},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5097550749778748},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5059108138084412},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.46266794204711914},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46088907122612},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.46067413687705994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44572460651397705},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42312347888946533},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41881299018859863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38179337978363037},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.19739821553230286},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3126686.3126745","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3126686.3126745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the on Thematic Workshops of ACM Multimedia 2017","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W1514027499","https://openalex.org/W1536680647","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1845051632","https://openalex.org/W1861492603","https://openalex.org/W1866072925","https://openalex.org/W1902934009","https://openalex.org/W1903029394","https://openalex.org/W1921293667","https://openalex.org/W1932847118","https://openalex.org/W1977500159","https://openalex.org/W1987549167","https://openalex.org/W2000288463","https://openalex.org/W2007972815","https://openalex.org/W2055132753","https://openalex.org/W2081580037","https://openalex.org/W2097089247","https://openalex.org/W2097117768","https://openalex.org/W2100031962","https://openalex.org/W2108598243","https://openalex.org/W2155541015","https://openalex.org/W2163605009","https://openalex.org/W2179352600","https://openalex.org/W2194775991","https://openalex.org/W2205224283","https://openalex.org/W2250384498","https://openalex.org/W2274287116","https://openalex.org/W2277195237","https://openalex.org/W2279098554","https://openalex.org/W2300242332","https://openalex.org/W2577784528","https://openalex.org/W2949117887","https://openalex.org/W2949605076","https://openalex.org/W2953236957","https://openalex.org/W2962749380"],"related_works":["https://openalex.org/W3139213884","https://openalex.org/W4317548404","https://openalex.org/W3022007134","https://openalex.org/W2130553454","https://openalex.org/W160673860","https://openalex.org/W2033364610","https://openalex.org/W2797776314","https://openalex.org/W3163689946","https://openalex.org/W4313561330","https://openalex.org/W4308757581"],"abstract_inverted_index":{"Automated":[0],"photo":[1,60,65],"tagging":[2,61],"has":[3],"established":[4],"itself":[5],"as":[6],"one":[7],"of":[8,13,35,96,99,125,154,166],"the":[9,75,94,122,139,164],"most":[10,79],"compelling":[11],"applications":[12],"deep":[14,17],"learning.":[15],"While":[16],"convolutional":[18],"neural":[19],"networks":[20],"have":[21],"repeatedly":[22],"demonstrated":[23],"top":[24],"performance":[25,118],"on":[26,119,128],"standard":[27,123],"datasets":[28],"for":[29,63,88,102,108,163],"classification,":[30],"there":[31],"are":[32],"a":[33,46,58,151],"number":[34],"often":[36],"overlooked":[37],"but":[38],"important":[39],"considerations":[40],"when":[41,150],"deploying":[42],"this":[43,50,114],"technology":[44],"in":[45,56,170],"real-world":[47,109],"scenario.":[48],"In":[49,134],"paper,":[51],"we":[52,136,161],"present":[53],"our":[54,81],"efforts":[55],"developing":[57],"large-scale":[59,171],"system":[62],"Flickr":[64],"search.":[66],"We":[67],"discuss":[68],"topics":[69],"including":[70],"how":[71],"to":[72,80],"1)":[73],"select":[74],"tags":[76],"that":[77,138],"matter":[78],"users;":[82],"2)":[83],"develop":[84],"lightweight,":[85],"high-performance":[86],"models":[87,140],"tag":[89],"prediction;":[90],"and":[91,131],"3)":[92],"leverage":[93],"power":[95],"large":[97],"amounts":[98],"noisy":[100,115],"data":[101,116,130,144,156,169],"training.":[103],"Our":[104],"results":[105,149],"demonstrate":[106],"that,":[107],"datasets,":[110],"training":[111],"exclusively":[112],"with":[113,121,142],"yields":[117],"par":[120],"paradigm":[124],"first":[126],"pre-training":[127],"clean":[129,155],"then":[132],"fine-tuning.":[133],"addition,":[135],"observe":[137],"trained":[141],"user-generated":[143,168],"can":[145],"yield":[146],"better":[147],"fine-tuning":[148],"small":[152],"amount":[153],"is":[157],"available.":[158],"As":[159],"such,":[160],"advocate":[162],"approach":[165],"harnessing":[167],"systems.":[172]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}