{"id":"https://openalex.org/W7119498578","doi":"https://doi.org/10.1007/s11063-025-11829-8","title":"Heterogeneous Gap Bridging in Cross-Media Retrieval via Deep Association Learning with Joint Distribution and Semantic Alignments","display_name":"Heterogeneous Gap Bridging in Cross-Media Retrieval via Deep Association Learning with Joint Distribution and Semantic Alignments","publication_year":2026,"publication_date":"2026-01-08","ids":{"openalex":"https://openalex.org/W7119498578","doi":"https://doi.org/10.1007/s11063-025-11829-8"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-025-11829-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11829-8","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s11063-025-11829-8","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057343819","display_name":"L Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210110925","display_name":"Jiaozuo University","ror":"https://ror.org/024nbxn35","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110925"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Li","raw_affiliation_strings":["Information Engineering School Jiaozuo Normal College, Jiaozuo, 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering School Jiaozuo Normal College, Jiaozuo, 454000, China","institution_ids":["https://openalex.org/I4210110925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100340794","display_name":"Xiaoliang Zhang","orcid":"https://orcid.org/0000-0001-9313-8428"},"institutions":[{"id":"https://openalex.org/I4210110925","display_name":"Jiaozuo University","ror":"https://ror.org/024nbxn35","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110925"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoliang Zhang","raw_affiliation_strings":["Information Engineering School Jiaozuo Normal College, Jiaozuo, 454000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering School Jiaozuo Normal College, Jiaozuo, 454000, China","institution_ids":["https://openalex.org/I4210110925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057343819"],"corresponding_institution_ids":["https://openalex.org/I4210110925"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":7.2205,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92576338,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"58","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.44350001215934753,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.44350001215934753,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.2282000035047531,"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":0.07020000368356705,"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/bridging","display_name":"Bridging (networking)","score":0.8324999809265137},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.6657999753952026},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5702000260353088},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.478300005197525},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.4706999957561493},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.46880000829696655},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46540001034736633},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.438400000333786}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.840399980545044},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.8324999809265137},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.6657999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6485999822616577},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5702000260353088},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.478300005197525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47440001368522644},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.4706999957561493},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.46880000829696655},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3314000070095062},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2833999991416931},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27900001406669617},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-025-11829-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11829-8","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-025-11829-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11829-8","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6228837966918945,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2911926260","https://openalex.org/W2915533878","https://openalex.org/W2946675767","https://openalex.org/W2947760388","https://openalex.org/W2987671777","https://openalex.org/W3006871679","https://openalex.org/W3006962461","https://openalex.org/W3017098848","https://openalex.org/W3027622815","https://openalex.org/W3043019877","https://openalex.org/W3081278515","https://openalex.org/W3108514068","https://openalex.org/W3137642335","https://openalex.org/W3154065069","https://openalex.org/W3166287017","https://openalex.org/W3172793889","https://openalex.org/W3187014459","https://openalex.org/W3205331935","https://openalex.org/W4200631412","https://openalex.org/W4206430846","https://openalex.org/W4224236022","https://openalex.org/W4311892932","https://openalex.org/W4321495289","https://openalex.org/W4353090144"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,6,20,32,36,56],"Internet":[3],"technologies,":[4],"particularly":[5],"social":[7],"networks":[8],"such":[9],"as":[10],"Weibo":[11],"and":[12,27,89,123,133],"Douban,":[13],"have":[14],"led":[15],"to":[16,47,102,127,148,179],"a":[17,65,96,114],"substantial":[18],"increase":[19],"multimodal":[21],"data,":[22],"including":[23],"images,":[24],"videos,":[25,86],"audio,":[26,88],"text.":[28],"This":[29],"has":[30],"resulted":[31],"growing":[33],"research":[34],"interest":[35],"multimedia":[37,84],"information":[38,106,142],"retrieval,":[39],"with":[40],"particular":[41],"focus":[42],"on":[43,71,162],"cross-media":[44,57,97,116,129,157],"retrieval.":[45,58],"Central":[46],"this":[48,61],"study":[49],"is":[50],"addressing":[51],"the":[52,72,144,150,163,168],"\u201cheterogeneous":[53],"gap\u201d":[54],"problem":[55],"To":[59],"address":[60],"challenge,":[62],"we":[63,94,112,138],"introduce":[64],"deep":[66,77],"association":[67,117,145],"learning":[68,146],"method":[69,170],"based":[70],"nonlinear":[73],"modeling":[74],"capabilities":[75],"of":[76],"neural":[78,99],"networks.":[79],"Our":[80],"approach":[81],"integrates":[82],"five":[83],"types\u2014images,":[85],"text,":[87],"3D":[90],"models\u2014for":[91],"cross-retrieval.":[92],"First,":[93],"employ":[95],"recurrent":[98],"network":[100],"(RNN)":[101],"capture":[103],"fine-grained":[104],"contextual":[105],"within":[107,132],"different":[108],"media":[109,135],"types.":[110,136],"Second,":[111],"propose":[113],"joint":[115],"loss":[118],"function":[119],"that":[120,167],"combines":[121],"distributional":[122],"semantic":[124,140,152],"alignment":[125],"mechanisms":[126],"learn":[128],"associations":[130],"both":[131],"across":[134],"Third,":[137],"incorporate":[139],"category":[141],"into":[143],"process":[147],"enhance":[149],"model\u2019s":[151],"discrimination":[153],"capability,":[154],"thereby":[155],"improving":[156],"retrieval":[158,182],"accuracy.":[159],"Experimental":[160],"results":[161],"XMediaNet":[164],"dataset":[165],"demonstrate":[166],"proposed":[169],"achieves":[171],"higher":[172],"mean":[173],"average":[174],"precision":[175],"(mAP)":[176],"values":[177],"compared":[178],"existing":[180],"cross-modal":[181],"methods.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-01-09T00:00:00"}
