{"id":"https://openalex.org/W2045218197","doi":"https://doi.org/10.1145/1878151.1878156","title":"Image tagging and search","display_name":"Image tagging and search","publication_year":2010,"publication_date":"2010-10-25","ids":{"openalex":"https://openalex.org/W2045218197","doi":"https://doi.org/10.1145/1878151.1878156","mag":"2045218197"},"language":"en","primary_location":{"id":"doi:10.1145/1878151.1878156","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1878151.1878156","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of second ACM SIGMM workshop on Social media","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/A5037268828","display_name":"Adrian Popescu","orcid":"https://orcid.org/0000-0002-8099-824X"},"institutions":[{"id":"https://openalex.org/I205703379","display_name":"Institut Mines-T\u00e9l\u00e9com","ror":"https://ror.org/025vp2923","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Adrian Popescu","raw_affiliation_strings":["Institut TELECOM/TELECOM Bretagne, Brest, France","Institut Telecom Telecom Bretagne, Brest, France#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut TELECOM/TELECOM Bretagne, Brest, France","institution_ids":["https://openalex.org/I205703379"]},{"raw_affiliation_string":"Institut Telecom Telecom Bretagne, Brest, France#TAB#","institution_ids":["https://openalex.org/I205703379"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039513155","display_name":"Gregory Grefenstette","orcid":"https://orcid.org/0000-0001-8479-049X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gregory Grefenstette","raw_affiliation_strings":["Exalead, Paris, France","Exalead, paris, France#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Exalead, Paris, France","institution_ids":[]},{"raw_affiliation_string":"Exalead, paris, France#TAB#","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.989300012588501,"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":0.9886999726295471,"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":0.7110217213630676},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6945990920066833},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6795787811279297},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.5741266012191772},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5732240080833435},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.47493770718574524},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.4180067777633667},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4153793156147003},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2715451717376709},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17061945796012878},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10690784454345703},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08416366577148438}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7110217213630676},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6945990920066833},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6795787811279297},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5741266012191772},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5732240080833435},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47493770718574524},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.4180067777633667},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4153793156147003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2715451717376709},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17061945796012878},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10690784454345703},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08416366577148438},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1878151.1878156","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1878151.1878156","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of second ACM SIGMM workshop on Social media","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W168087971","https://openalex.org/W1812735916","https://openalex.org/W1965067550","https://openalex.org/W1990843604","https://openalex.org/W2063205814","https://openalex.org/W2103388840","https://openalex.org/W2103467710","https://openalex.org/W2114822471","https://openalex.org/W2118573581","https://openalex.org/W2136029705","https://openalex.org/W2145500920","https://openalex.org/W2148698197","https://openalex.org/W2154288935","https://openalex.org/W2154331289","https://openalex.org/W2176304865","https://openalex.org/W2905598695","https://openalex.org/W2914740575"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W4234874385","https://openalex.org/W2369710579","https://openalex.org/W2323648130","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1990856605","https://openalex.org/W2151762367"],"abstract_inverted_index":{"Social":[0],"computing":[1],"sites":[2],"constitute":[3],"a":[4,59,98,113,123,149,154],"valuable":[5],"source":[6],"of":[7,20,49,55,101,107,131,143,151],"user-generated":[8],"content":[9,16,22],"for":[10,157],"user":[11,14,50,63],"modeling.":[12],"Whereas":[13],"generated":[15],"and":[17,42,72,79,84,119,147],"the":[18,32,36,47,53,105],"mining":[19],"such":[21],"are":[23,82,89],"well":[24],"studied,":[25],"little":[26],"attention":[27],"has":[28],"been":[29],"given":[30],"in":[31,97],"literature":[33],"to":[34,52,57,67,134],"modeling":[35],"relationship":[37],"between":[38,92],"users'":[39],"personal":[40],"information":[41],"content.":[43],"Here":[44],"we":[45,111],"analyze":[46],"relation":[48],"gender":[51,93,108,114,146],"choice":[54],"tags":[56],"describe":[58],"photo.":[60],"A":[61],"large":[62,99],"sample":[64],"is":[65],"examined":[66],"produce":[68],"gender-related":[69],"tagging":[70],"vocabularies":[71],"tag":[73,141],"representations.":[74],"1000":[75],"salient":[76],"tags'":[77],"male":[78],"female":[80],"representations":[81,142],"compared":[83],"results":[85,138],"indicate":[86],"that":[87,127,148],"there":[88],"important":[90],"differences":[91],"based":[94],"term":[95],"choices":[96],"majority":[100],"cases.":[102],"To":[103],"test":[104],"influence":[106],"on":[109],"retrieval,":[110],"built":[112],"sensitive":[115],"image":[116,136],"search":[117,137],"prototype":[118],"tested":[120],"it,":[121],"using":[122,140],"survey.":[124],"Results":[125],"show":[126],"around":[128],"two":[129],"thirds":[130],"participants":[132,152],"tend":[133],"prefer":[135],"obtained":[139],"their":[144,158],"own":[145,159],"third":[150],"have":[153],"clear":[155],"preference":[156],"gender's":[160],"results.":[161]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
