{"id":"https://openalex.org/W1973292592","doi":"https://doi.org/10.1145/2814815.2814818","title":"Building User Profiles from Shared Photos","display_name":"Building User Profiles from Shared Photos","publication_year":2015,"publication_date":"2015-10-30","ids":{"openalex":"https://openalex.org/W1973292592","doi":"https://doi.org/10.1145/2814815.2814818","mag":"1973292592"},"language":"en","primary_location":{"id":"doi:10.1145/2814815.2814818","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2814815.2814818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Workshop on Community-Organized Multimodal Mining: Opportunities for Novel Solutions","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/A5103960169","display_name":"Dhiraj Joshi","orcid":null},"institutions":[{"id":"https://openalex.org/I26274970","display_name":"FX Palo Alto Laboratory","ror":"https://ror.org/05ef4zt88","country_code":"US","type":"facility","lineage":["https://openalex.org/I26274970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dhiraj Joshi","raw_affiliation_strings":["FXPAL, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FXPAL, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I26274970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069841532","display_name":"Matthew Cooper","orcid":"https://orcid.org/0000-0003-2395-8628"},"institutions":[{"id":"https://openalex.org/I26274970","display_name":"FX Palo Alto Laboratory","ror":"https://ror.org/05ef4zt88","country_code":"US","type":"facility","lineage":["https://openalex.org/I26274970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Cooper","raw_affiliation_strings":["FXPAL, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FXPAL, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I26274970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025376488","display_name":"Francine Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I26274970","display_name":"FX Palo Alto Laboratory","ror":"https://ror.org/05ef4zt88","country_code":"US","type":"facility","lineage":["https://openalex.org/I26274970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Francine Chen","raw_affiliation_strings":["FXPAL, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FXPAL, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I26274970"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041192765","display_name":"Yanying Chen","orcid":"https://orcid.org/0000-0001-5034-5312"},"institutions":[{"id":"https://openalex.org/I26274970","display_name":"FX Palo Alto Laboratory","ror":"https://ror.org/05ef4zt88","country_code":"US","type":"facility","lineage":["https://openalex.org/I26274970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan-ying Chen","raw_affiliation_strings":["FXPAL, Palo Alto, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FXPAL, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I26274970"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1872,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57412877,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"42"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9991999864578247,"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":0.9973000288009644,"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":0.7553288340568542},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6929015517234802},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5819607377052307},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5780832767486572},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5569955110549927},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5304462313652039},{"id":"https://openalex.org/keywords/user-group","display_name":"User group","score":0.432686448097229},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4222368597984314},{"id":"https://openalex.org/keywords/rank-correlation","display_name":"Rank correlation","score":0.4145030379295349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3711117208003998},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33812642097473145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33511030673980713},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.21066784858703613},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20532295107841492},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20142805576324463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.139398992061615}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7553288340568542},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6929015517234802},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5819607377052307},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5780832767486572},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5569955110549927},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5304462313652039},{"id":"https://openalex.org/C3017738328","wikidata":"https://www.wikidata.org/wiki/Q613366","display_name":"User group","level":2,"score":0.432686448097229},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4222368597984314},{"id":"https://openalex.org/C101601086","wikidata":"https://www.wikidata.org/wiki/Q3753228","display_name":"Rank correlation","level":2,"score":0.4145030379295349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3711117208003998},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33812642097473145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33511030673980713},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.21066784858703613},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20532295107841492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20142805576324463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.139398992061615},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2814815.2814818","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2814815.2814818","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Workshop on Community-Organized Multimodal Mining: Opportunities for Novel Solutions","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1172683934","https://openalex.org/W1532325895","https://openalex.org/W1544092585","https://openalex.org/W1985514943","https://openalex.org/W2053101950","https://openalex.org/W2074822122","https://openalex.org/W2078483536","https://openalex.org/W2088345367","https://openalex.org/W2096130203","https://openalex.org/W2117539524","https://openalex.org/W2119957187","https://openalex.org/W2122704742","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2165232124","https://openalex.org/W2604272474","https://openalex.org/W4213009331","https://openalex.org/W6627816076","https://openalex.org/W6646664084"],"related_works":["https://openalex.org/W2485872624","https://openalex.org/W2112835755","https://openalex.org/W4291951920","https://openalex.org/W2349674371","https://openalex.org/W2097495471","https://openalex.org/W1696545756","https://openalex.org/W3093637834","https://openalex.org/W2379367937","https://openalex.org/W2490353053","https://openalex.org/W2071581267"],"abstract_inverted_index":{"In":[0,75],"this":[1],"paper,":[2],"we":[3,89,167],"analyze":[4],"the":[5,80,118,132,141,152,156,161],"association":[6],"between":[7],"a":[8,56,95,178],"social":[9,65,73,87],"media":[10],"user's":[11],"photo":[12],"content":[13,18],"and":[14,127,136,174],"their":[15,49,72,171],"interests.":[16,74],"Visual":[17],"of":[19,134],"photos":[20,50],"is":[21,107,125,129],"analyzed":[22],"using":[23,160,177],"state-of-the-art":[24],"deep":[25],"learning":[26],"based":[27,58,99],"automatic":[28],"concept":[29,36],"recognition.":[30],"We":[31,62,149],"compute":[32],"an":[33,76],"aggregate":[34],"visual":[35,135,153,172],"signature":[37,59],"for":[38],"each":[39],"user.":[40,61],"User":[41],"tags":[42],"that":[43,67,110,131],"have":[44],"been":[45],"manually":[46],"applied":[47],"to":[48,54,70,78],"are":[51],"also":[52,63,108,150],"used":[53],"construct":[55],"tf-idf":[57],"per":[60],"obtain":[64],"groups":[66,111],"users":[68,112,169],"join":[69],"represent":[71],"effort":[77],"compare":[79,90],"visual-based":[81],"versus":[82],"tag-based":[83],"user":[84],"profiles":[85],"with":[86,94],"interests,":[88],"corresponding":[91],"similarity":[92,97,143,159],"matrices":[93],"reference":[96,157],"matrix":[98,144],"on":[100],"users'":[101],"group":[102,120],"memberships.":[103],"A":[104,122],"random":[105,114],"baseline":[106],"included":[109],"by":[113,170],"sampling":[115],"while":[116],"preserving":[117],"actual":[119],"sizes.":[121],"difference":[123],"metric":[124],"proposed":[126],"it":[128],"shown":[130],"combination":[133],"text":[137],"features":[138],"better":[139],"approximates":[140],"group-based":[142],"than":[145],"either":[146],"modality":[147],"individually.":[148],"validate":[151],"analysis":[154],"against":[155],"inter-user":[158],"Spearman":[162],"rank":[163,175],"correlation":[164],"coefficient.":[165],"Finally":[166],"cluster":[168,179],"signatures":[173],"clusters":[176],"uniqueness":[180],"criteria.":[181]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
