{"id":"https://openalex.org/W3163793743","doi":"https://doi.org/10.1109/access.2021.3080976","title":"Semi-Supervised Learning Based Semantic Cross-Media Retrieval","display_name":"Semi-Supervised Learning Based Semantic Cross-Media Retrieval","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3163793743","doi":"https://doi.org/10.1109/access.2021.3080976","mag":"3163793743"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3080976","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3080976","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09432800.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09432800.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006832306","display_name":"Xiyuan Zheng","orcid":"https://orcid.org/0000-0002-3604-4190"},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiyuan Zheng","raw_affiliation_strings":["School of Data Science and Computer Science, Shandong Women\u2019s University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer Science, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103086580","display_name":"Wei Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I4210106451","display_name":"Jinan Central Hospital","ror":"https://ror.org/01fr19c68","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210106451"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhu","raw_affiliation_strings":["Jinan Central Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jinan Central Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455","https://openalex.org/I4210106451"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070531457","display_name":"Zhenmei Yu","orcid":"https://orcid.org/0000-0003-1899-0850"},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenmei Yu","raw_affiliation_strings":["School of Data Science and Computer Science, Shandong Women\u2019s University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer Science, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078389239","display_name":"Meijia Zhang","orcid":"https://orcid.org/0000-0002-2957-6359"},"institutions":[{"id":"https://openalex.org/I4210151294","display_name":"Shandong Women\u2019s University","ror":"https://ror.org/03rp8h078","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151294"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meijia Zhang","raw_affiliation_strings":["School of Data Science and Computer Science, Shandong Women\u2019s University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-2957-6359","affiliations":[{"raw_affiliation_string":"School of Data Science and Computer Science, Shandong Women\u2019s University, Jinan, China","institution_ids":["https://openalex.org/I4210151294"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.1808,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44661592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"9","issue":null,"first_page":"75049","last_page":"75057"},"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":0.9995999932289124,"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":0.9983999729156494,"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":0.901870608329773},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5558936595916748},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5410690307617188},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.529848575592041},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44064366817474365},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4385475516319275},{"id":"https://openalex.org/keywords/multimedia-information-retrieval","display_name":"Multimedia information retrieval","score":0.43335095047950745},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43131259083747864},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4164281189441681},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33469921350479126},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1771581768989563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.901870608329773},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5558936595916748},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5410690307617188},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.529848575592041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44064366817474365},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4385475516319275},{"id":"https://openalex.org/C2776318140","wikidata":"https://www.wikidata.org/wiki/Q6934776","display_name":"Multimedia information retrieval","level":2,"score":0.43335095047950745},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43131259083747864},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4164281189441681},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33469921350479126},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1771581768989563},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/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":2,"locations":[{"id":"doi:10.1109/access.2021.3080976","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3080976","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09432800.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b26ba072c44c49f290d26533a2c997ce","is_oa":true,"landing_page_url":"https://doaj.org/article/b26ba072c44c49f290d26533a2c997ce","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 75049-75057 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3080976","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3080976","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09432800.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3163793743.pdf","grobid_xml":"https://content.openalex.org/works/W3163793743.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1123427201","https://openalex.org/W1202352811","https://openalex.org/W1523385540","https://openalex.org/W1538281814","https://openalex.org/W1970855969","https://openalex.org/W2013535308","https://openalex.org/W2038158923","https://openalex.org/W2042969131","https://openalex.org/W2070753207","https://openalex.org/W2071207147","https://openalex.org/W2081877265","https://openalex.org/W2081944951","https://openalex.org/W2100235303","https://openalex.org/W2106277773","https://openalex.org/W2114456882","https://openalex.org/W2119775030","https://openalex.org/W2145291599","https://openalex.org/W2170653751","https://openalex.org/W2210322478","https://openalex.org/W2212216676","https://openalex.org/W2216674905","https://openalex.org/W2294512729","https://openalex.org/W2397674542","https://openalex.org/W2412038070","https://openalex.org/W2476034201","https://openalex.org/W2524618402","https://openalex.org/W2626052180","https://openalex.org/W2752038076","https://openalex.org/W2897135094","https://openalex.org/W2929255686","https://openalex.org/W2946675767","https://openalex.org/W3148981562","https://openalex.org/W6631216910","https://openalex.org/W6697020685","https://openalex.org/W6712554547","https://openalex.org/W6721087566"],"related_works":["https://openalex.org/W2393699422","https://openalex.org/W2168037874","https://openalex.org/W2387268739","https://openalex.org/W4250138412","https://openalex.org/W2135728080","https://openalex.org/W2379546782","https://openalex.org/W2534443799","https://openalex.org/W2148968119","https://openalex.org/W2105240677","https://openalex.org/W2391460410"],"abstract_inverted_index":{"With":[0,28],"the":[1,4,29,34,53,71,75,111,126,129,133,137,143,171,185,198],"advent":[2],"of":[3,6,31,52,74,117,125,132],"era":[5],"big":[7],"data,":[8,33],"information":[9,73,131],"has":[10],"gradually":[11],"changed":[12],"from":[13],"a":[14,18,100,155],"single":[15],"modal":[16],"to":[17,44,91,121,183],"diversified":[19],"form,":[20],"such":[21],"as":[22],"image,":[23],"text,":[24],"video,":[25],"audio,":[26],"etc.":[27],"growth":[30],"multimedia":[32,47],"key":[35],"problem":[36],"faced":[37],"by":[38],"cross-media":[39,59,157,204],"retrieval":[40,60,205],"technology":[41],"is":[42,84,87,120,181],"how":[43],"quickly":[45],"retrieve":[46],"data":[48,76],"with":[49,163,179],"different":[50],"modalities":[51],"same":[54],"semantic.":[55],"At":[56],"present,":[57],"many":[58],"techniques":[61],"use":[62,124],"local":[63],"annotated":[64],"samples":[65,135],"for":[66],"training.":[67],"In":[68],"this":[69,97,118],"way,":[70],"semantic":[72,130],"cannot":[77],"be":[78],"fully":[79],"utilized,":[80],"and":[81,93,136,150,166],"manual":[82],"annotation":[83],"required,":[85],"which":[86],"rather":[88],"labor-intensive":[89],"prone":[90],"errors":[92],"subjective":[94],"viewing.":[95],"Therefore,":[96],"paper":[98],"proposes":[99],"Semi-Supervised":[101],"learning":[102,158],"based":[103],"Semantic":[104],"Cross-Media":[105],"Retrieval":[106],"(S3CMR)":[107],"method":[108,119,177,200],"aiming":[109],"at":[110],"above":[112],"problems.":[113],"The":[114],"main":[115],"advantage":[116],"make":[122],"full":[123],"relationship":[127],"between":[128],"labeled":[134],"unlabeled":[138],"samples.":[139],"Simultaneously,":[140],"we":[141],"integrate":[142],"linear":[144],"regression":[145],"term,":[146,149],"correlation":[147],"analysis":[148],"feature":[151],"selection":[152],"term":[153],"into":[154],"joint":[156],"framework.":[159],"These":[160],"terms":[161],"interact":[162],"each":[164],"other":[165],"embed":[167],"more":[168],"semantics":[169],"in":[170],"shared":[172],"subspace.":[173],"Furthermore,":[174],"an":[175],"iterative":[176],"guaranteed":[178],"convergence":[180],"proposed":[182,199],"solve":[184],"formulated":[186],"optimization":[187],"problem.":[188],"Experimental":[189],"results":[190],"on":[191],"three":[192],"publicly":[193],"available":[194],"datasets":[195],"demonstrate":[196],"that":[197],"outperforms":[201],"eight":[202],"state-of-the-art":[203],"methods.":[206]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
