{"id":"https://openalex.org/W2782689416","doi":"https://doi.org/10.1109/bigdata.2017.8257972","title":"Exploiting visual and textual neighborhood information to improve image-tag relevance","display_name":"Exploiting visual and textual neighborhood information to improve image-tag relevance","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2782689416","doi":"https://doi.org/10.1109/bigdata.2017.8257972","mag":"2782689416"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8257972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8257972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","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/A5066177122","display_name":"Chandramani Chaudhary","orcid":null},"institutions":[{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Chandramani Chaudhary","raw_affiliation_strings":["Department of Computer Science and Information Systems, BITS Pilani, Pilani, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Systems, BITS Pilani, Pilani, India","institution_ids":["https://openalex.org/I74796645"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027120172","display_name":"Poonam Goyal","orcid":"https://orcid.org/0000-0003-1556-9905"},"institutions":[{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Poonam Goyal","raw_affiliation_strings":["Department of Computer Science and Information Systems, BITS Pilani, Pilani, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Systems, BITS Pilani, Pilani, India","institution_ids":["https://openalex.org/I74796645"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100728316","display_name":"Yi\u2010Ping Phoebe Chen","orcid":"https://orcid.org/0000-0002-4122-3767"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yi-Ping Phoebe Chen","raw_affiliation_strings":["Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I196829312"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066177122"],"corresponding_institution_ids":["https://openalex.org/I74796645"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49916789,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"72","issue":null,"first_page":"566","last_page":"575"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9972000122070312,"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":0.8419119715690613},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.8013274073600769},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.7802995443344116},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7339234948158264},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6606236696243286},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6498334407806396},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6252253651618958},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.5775132775306702},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5404345393180847},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5147805213928223},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.48765480518341064},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38103917241096497},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37755927443504333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8419119715690613},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.8013274073600769},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.7802995443344116},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7339234948158264},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6606236696243286},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6498334407806396},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6252253651618958},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.5775132775306702},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5404345393180847},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5147805213928223},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.48765480518341064},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38103917241096497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37755927443504333},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8257972","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8257972","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1552767446","https://openalex.org/W1686810756","https://openalex.org/W1956559956","https://openalex.org/W1964536038","https://openalex.org/W1964810009","https://openalex.org/W1974145285","https://openalex.org/W1975878180","https://openalex.org/W1983988843","https://openalex.org/W1990843604","https://openalex.org/W2007972815","https://openalex.org/W2014854862","https://openalex.org/W2018590080","https://openalex.org/W2020969339","https://openalex.org/W2031880589","https://openalex.org/W2037328854","https://openalex.org/W2049632392","https://openalex.org/W2057503255","https://openalex.org/W2082456243","https://openalex.org/W2087560337","https://openalex.org/W2093301878","https://openalex.org/W2100476178","https://openalex.org/W2103892759","https://openalex.org/W2104158084","https://openalex.org/W2110226872","https://openalex.org/W2118597426","https://openalex.org/W2124916819","https://openalex.org/W2148698197","https://openalex.org/W2155803963","https://openalex.org/W2161258050","https://openalex.org/W2170942078","https://openalex.org/W2294281382","https://openalex.org/W2325227998","https://openalex.org/W2336668576","https://openalex.org/W2408291668","https://openalex.org/W2413850928","https://openalex.org/W2536305071","https://openalex.org/W2913081710","https://openalex.org/W2962835968","https://openalex.org/W2963240457","https://openalex.org/W3104069527","https://openalex.org/W6632992187","https://openalex.org/W6655071158","https://openalex.org/W6702993526"],"related_works":["https://openalex.org/W3177930984","https://openalex.org/W2052697133","https://openalex.org/W2076896210","https://openalex.org/W2111630109","https://openalex.org/W2384288472","https://openalex.org/W1539573266","https://openalex.org/W2093596879","https://openalex.org/W2376984068","https://openalex.org/W2201969175","https://openalex.org/W2747088704"],"abstract_inverted_index":{"Many":[0],"applications,":[1],"such":[2,186],"as":[3,187],"image":[4,6,9,163],"searching,":[5],"indexing,":[7],"and":[8,29,71,136,160,179,190],"label":[10],"recommendations,":[11],"have":[12],"started":[13],"using":[14],"tagged":[15],"images":[16,70],"to":[17,25,57,138,153,167],"benefit":[18],"from":[19],"user":[20],"input.":[21],"However,":[22],"tags":[23,32,56,85,122],"tend":[24],"be":[26],"imprecise,":[27],"incomplete,":[28],"ambiguous.":[30],"Moreover,":[31],"are":[33,174],"also":[34,130],"biased":[35],"towards":[36],"the":[37,42,49,81,91,127,140,168],"user's":[38],"perspective":[39],"which":[40,103],"degrades":[41],"performance":[43],"of":[44,48,69,74,83,86,90,113,115,123,126],"tag-based":[45],"systems.":[46],"Most":[47,89],"existing":[50],"methods":[51],"use":[52],"visual":[53,67,124],"neighborhoods":[54],"and/or":[55],"estimate":[58],"image-tag":[59,63,92],"relevance.":[60],"We":[61,129],"improve":[62],"relevance":[64,93],"by":[65,120],"combining":[66],"neighborhood":[68,73],"textual":[72],"tags.":[75,141],"By":[76],"doing":[77],"this,":[78],"we":[79],"boost":[80],"ranking":[82,159],"informative":[84],"an":[87],"image.":[88],"measures":[94],"work":[95],"well":[96],"when":[97],"large":[98],"supporting":[99],"data":[100],"is":[101,104,118],"available,":[102],"typically":[105],"not":[106],"sufficient":[107],"in":[108,157,162],"real":[109],"datasets.":[110],"This":[111],"problem":[112],"Void":[114],"Information":[116],"(VoI)":[117],"addressed":[119],"exploiting":[121],"neighbors":[125],"images.":[128],"exploit":[131],"external":[132],"resources":[133],"like":[134],"Wikipedia":[135],"WordNet":[137],"strengthen":[139],"The":[142,172],"proposed":[143],"approach,":[144],"TVNTag":[145],"(Textual":[146],"Visual":[147],"Neighborhood":[148],"based":[149],"Tag)":[150],"exhibits":[151],"up":[152],"46.1%":[154],"relative":[155],"improvement":[156],"tag":[158],"79.5%":[161],"ranking,":[164],"with":[165],"respect":[166],"current":[169],"state-of-the-art":[170],"methods.":[171],"experiments":[173],"conducted":[175],"for":[176],"different":[177],"tasks":[178],"evaluation":[180],"scenarios":[181],"on":[182],"benchmarked":[183],"social":[184],"data,":[185],"MIRFlickr,":[188],"NUS-WIDE,":[189],"train10k.":[191]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
