乐胖代购免代理版

{"id":"https://openalex.org/W4399139324","doi":"https://doi.org/10.1007/s11063-024-11641-w","title":"Multichannel Multimodal Emotion Analysis of Cross-Modal Feedback Interactions Based on Knowledge Graph","display_name":"Multichannel Multimodal Emotion Analysis of Cross-Modal Feedback Interactions Based on Knowledge Graph","publication_year":2024,"publication_date":"2024-05-29","ids":{"openalex":"https://openalex.org/W4399139324","doi":"https://doi.org/10.1007/s11063-024-11641-w"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-024-11641-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11641-w.pdf","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_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11641-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100630430","display_name":"Shaohua Dong","orcid":"https://orcid.org/0009-0008-2685-6217"},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"funder","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Dong","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang Normal University, \u00dcr\u00fcmqi, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang Normal University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I1334729051"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062877752","display_name":"Xiaochao Fan","orcid":"https://orcid.org/0000-0003-4615-5131"},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"funder","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochao Fan","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang Normal University, \u00dcr\u00fcmqi, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang Normal University, \u00dcr\u00fcmqi, China","institution_ids":["https://openalex.org/I1334729051"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101368634","display_name":"Xinchun Ma","orcid":null},"institutions":[],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinchun Ma","raw_affiliation_strings":["XinJiang Electronic Research Institute, \u00dcr\u00fcmqi, China"],"affiliations":[{"raw_affiliation_string":"XinJiang Electronic Research Institute, \u00dcr\u00fcmqi, China","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":3.058,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.999981,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":"56","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9893,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9893,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9886,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9473,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6601572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4994421},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43293697},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.41230807},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.3252572},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14665791},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.050481886},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-024-11641-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11641-w.pdf","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_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-024-11641-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-024-11641-w.pdf","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_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319965","https://openalex.org/P4310319900"],"host_organization_lineage_names":["Springer Nature","Springer Science+Business Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":26,"referenced_works":["https://openalex.org/W1984676746","https://openalex.org/W2072007696","https://openalex.org/W2090777335","https://openalex.org/W2095176743","https://openalex.org/W2137704276","https://openalex.org/W2242874043","https://openalex.org/W2536583325","https://openalex.org/W2736282266","https://openalex.org/W2787581402","https://openalex.org/W2790309729","https://openalex.org/W2886444838","https://openalex.org/W2962931510","https://openalex.org/W2964010806","https://openalex.org/W2964216663","https://openalex.org/W2964285257","https://openalex.org/W2964346351","https://openalex.org/W2993259699","https://openalex.org/W3016463114","https://openalex.org/W3034266838","https://openalex.org/W3044187822","https://openalex.org/W3173549566","https://openalex.org/W3174517569","https://openalex.org/W4221155339","https://openalex.org/W4221155388","https://openalex.org/W4375869329","https://openalex.org/W4389523777"],"related_works":["https://openalex.org/W4396701345","https://openalex.org/W4396696052","https://openalex.org/W4395014643","https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2382290278","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Abstract":[0],"Multimodal":[1],"sentiment":[2,10,21,65,72,101],"analysis":[3,11,22,73],"is":[4,46,181],"a":[5,88,130,176],"downstream":[6],"branch":[7],"task":[8],"of":[9,30,58,107,139,200],"with":[12],"high":[13],"attention":[14],"at":[15],"present.":[16],"Previous":[17],"work":[18],"in":[19,167,198],"multimodal":[20,100,185],"have":[23],"focused":[24],"on":[25],"the":[26,33,56,96,111,118,151,168],"representation":[27],"and":[28,117,142,202,209],"fusion":[29,179],"modalities,":[31],"capturing":[32,123],"underlying":[34],"semantic":[35,164],"relationships":[36],"between":[37],"modalities":[38],"by":[39],"considering":[40],"contextual":[41,50],"information.":[42,66,125],"While":[43],"this":[44],"approach":[45],"feasible":[47],"for":[48,122,183],"simple":[49],"comments,":[51],"more":[52,63],"complex":[53],"comments":[54],"require":[55],"integration":[57],"external":[59,69,119,159],"knowledge":[60,70,97,120,160,172],"to":[61,74,146,153,206],"obtain":[62],"accurate":[64],"However,":[67],"incorporating":[68],"into":[71,99],"enhance":[75],"information":[76,165,186],"complementarity":[77],"has":[78],"not":[79],"been":[80],"thoroughly":[81],"investigated.":[82],"To":[83],"address":[84],"this,":[85],"we":[86],"propose":[87],"multichannel":[89,184],"cross-modal":[90,112,127],"feedback":[91,113],"interaction":[92,115,128],"model":[93,105,152],"that":[94],"incorporates":[95],"graph":[98,161,173],"analysis.":[102],"Our":[103],"proposed":[104],"consists":[106],"two":[108,189],"main":[109],"components:":[110],"recurrent":[114],"module":[116,121,180],"latent":[124],"The":[126,158],"employs":[129],"self-feedback":[131],"mechanism":[132],"during":[133],"network":[134],"training,":[135],"extracting":[136],"feature":[137,156,178],"representations":[138,145,166],"each":[140],"modality":[141],"using":[143],"these":[144],"mask":[147],"sensory":[148],"inputs,":[149],"allowing":[150],"perform":[154],"feedback-based":[155],"masking.":[157],"captures":[162],"potential":[163],"textual":[169],"data":[170],"through":[171],"embedding.":[174],"Finally,":[175],"global":[177],"employed":[182],"integration.":[187],"On":[188],"publicly":[190],"available":[191],"datasets,":[192],"our":[193],"method":[194],"demonstrates":[195],"good":[196],"performance":[197],"terms":[199],"accuracy":[201],"F1":[203],"scores,":[204],"compared":[205],"state-of-the-art":[207],"models":[208],"several":[210],"baselines.":[211]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4399139324","counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-04-21T01:32:56.968571","created_date":"2024-05-30"}