{"id":"https://openalex.org/W3173504106","doi":"https://doi.org/10.1109/taffc.2021.3090040","title":"A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology","display_name":"A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology","publication_year":2021,"publication_date":"2021-06-23","ids":{"openalex":"https://openalex.org/W3173504106","doi":"https://doi.org/10.1109/taffc.2021.3090040","mag":"3173504106"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2021.3090040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2021.3090040","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-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/A5062621013","display_name":"Hao-Chun Yang","orcid":"https://orcid.org/0000-0003-3724-5055"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hao-Chun Yang","raw_affiliation_strings":["Electrical Engineering, National Tsing Hua University, Hsinchu City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-3724-5055","affiliations":[{"raw_affiliation_string":"Electrical Engineering, National Tsing Hua University, Hsinchu City, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086107623","display_name":"Chi-Chun Lee","orcid":"https://orcid.org/0000-0003-0186-4321"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Chun Lee","raw_affiliation_strings":["Electrical Engineering, National Tsing Hua University, Hsinchu City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-0186-4321","affiliations":[{"raw_affiliation_string":"Electrical Engineering, National Tsing Hua University, Hsinchu City, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":null,"fwci":0.6846,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.70224964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"14","issue":"2","first_page":"931","last_page":"943"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9915000200271606,"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"}},{"id":"https://openalex.org/T11040","display_name":"Personality Traits and Psychology","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/personality","display_name":"Personality","score":0.7482477426528931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6047099232673645},{"id":"https://openalex.org/keywords/trait","display_name":"Trait","score":0.5905096530914307},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5364720225334167},{"id":"https://openalex.org/keywords/big-five-personality-traits","display_name":"Big Five personality traits","score":0.5361335873603821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46992743015289307},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.46545034646987915},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.439956933259964},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4299313724040985},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3331077992916107},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.28080835938453674},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.13314804434776306},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.07527196407318115}],"concepts":[{"id":"https://openalex.org/C187288502","wikidata":"https://www.wikidata.org/wiki/Q641118","display_name":"Personality","level":2,"score":0.7482477426528931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6047099232673645},{"id":"https://openalex.org/C106934330","wikidata":"https://www.wikidata.org/wiki/Q1971873","display_name":"Trait","level":2,"score":0.5905096530914307},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5364720225334167},{"id":"https://openalex.org/C2865642","wikidata":"https://www.wikidata.org/wiki/Q378132","display_name":"Big Five personality traits","level":3,"score":0.5361335873603821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46992743015289307},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.46545034646987915},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.439956933259964},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4299313724040985},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3331077992916107},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.28080835938453674},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.13314804434776306},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.07527196407318115},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2021.3090040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2021.3090040","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5600000023841858}],"awards":[{"id":"https://openalex.org/G5309581825","display_name":null,"funder_award_id":"109-2634-F-007-012","funder_id":"https://openalex.org/F4320322108","funder_display_name":"Ministry of Science and Technology"},{"id":"https://openalex.org/G7983086163","display_name":null,"funder_award_id":"110-2634-F-007-012","funder_id":"https://openalex.org/F4320322108","funder_display_name":"Ministry of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320322108","display_name":"Ministry of Science and Technology","ror":"https://ror.org/032e49973"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":112,"referenced_works":["https://openalex.org/W111858957","https://openalex.org/W629663968","https://openalex.org/W744439142","https://openalex.org/W1165538689","https://openalex.org/W1239497932","https://openalex.org/W1583278551","https://openalex.org/W1969135658","https://openalex.org/W1974073092","https://openalex.org/W1999543972","https://openalex.org/W2003950529","https://openalex.org/W2004691622","https://openalex.org/W2014399678","https://openalex.org/W2034734862","https://openalex.org/W2036808384","https://openalex.org/W2070075376","https://openalex.org/W2071559616","https://openalex.org/W2077129354","https://openalex.org/W2085662862","https://openalex.org/W2089468765","https://openalex.org/W2089809964","https://openalex.org/W2093351294","https://openalex.org/W2101234009","https://openalex.org/W2101422898","https://openalex.org/W2131796923","https://openalex.org/W2133017516","https://openalex.org/W2135519336","https://openalex.org/W2147324912","https://openalex.org/W2162090451","https://openalex.org/W2187089797","https://openalex.org/W2200488194","https://openalex.org/W2267186426","https://openalex.org/W2268996352","https://openalex.org/W2282738454","https://openalex.org/W2293831950","https://openalex.org/W2293928919","https://openalex.org/W2299277274","https://openalex.org/W2400574415","https://openalex.org/W2408532633","https://openalex.org/W2476764015","https://openalex.org/W2488468968","https://openalex.org/W2489406233","https://openalex.org/W2502360140","https://openalex.org/W2507152649","https://openalex.org/W2515814097","https://openalex.org/W2547146855","https://openalex.org/W2574138591","https://openalex.org/W2576686289","https://openalex.org/W2599743206","https://openalex.org/W2610034660","https://openalex.org/W2619947201","https://openalex.org/W2731964405","https://openalex.org/W2740882943","https://openalex.org/W2752234714","https://openalex.org/W2785934082","https://openalex.org/W2789013551","https://openalex.org/W2790404832","https://openalex.org/W2794596256","https://openalex.org/W2796991503","https://openalex.org/W2804419299","https://openalex.org/W2806827751","https://openalex.org/W2888802106","https://openalex.org/W2889326414","https://openalex.org/W2905849635","https://openalex.org/W2918872075","https://openalex.org/W2945091618","https://openalex.org/W2953273646","https://openalex.org/W2962711740","https://openalex.org/W2962934715","https://openalex.org/W2963076818","https://openalex.org/W2964015378","https://openalex.org/W2964097678","https://openalex.org/W2969145558","https://openalex.org/W2971933740","https://openalex.org/W2973258416","https://openalex.org/W2979059511","https://openalex.org/W2979750740","https://openalex.org/W2980023663","https://openalex.org/W2980064575","https://openalex.org/W2982294548","https://openalex.org/W2985882473","https://openalex.org/W2989491368","https://openalex.org/W3015699742","https://openalex.org/W3016531141","https://openalex.org/W3018455418","https://openalex.org/W3021130378","https://openalex.org/W3024961463","https://openalex.org/W3048064517","https://openalex.org/W3098699623","https://openalex.org/W4210257598","https://openalex.org/W4240221596","https://openalex.org/W4385245566","https://openalex.org/W6604524798","https://openalex.org/W6621977841","https://openalex.org/W6675354045","https://openalex.org/W6687610758","https://openalex.org/W6713173407","https://openalex.org/W6714127899","https://openalex.org/W6724088355","https://openalex.org/W6726873649","https://openalex.org/W6732057686","https://openalex.org/W6732508302","https://openalex.org/W6736575291","https://openalex.org/W6739901393","https://openalex.org/W6747701563","https://openalex.org/W6754929296","https://openalex.org/W6755477022","https://openalex.org/W6762369869","https://openalex.org/W6765814706","https://openalex.org/W6767030246","https://openalex.org/W6767710714","https://openalex.org/W6807384801","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W2109986081","https://openalex.org/W4293226380","https://openalex.org/W2417308975","https://openalex.org/W4297589944","https://openalex.org/W2157908879","https://openalex.org/W3125957671","https://openalex.org/W2767446002","https://openalex.org/W2898389145","https://openalex.org/W1966488223","https://openalex.org/W2796384540"],"abstract_inverted_index":{"Physiological":[0],"automatic":[1,193],"personality":[2,12,35,51,89,158,172,194],"recognition":[3],"has":[4],"been":[5],"largely":[6],"developed":[7],"to":[8,48,57,106,129,189],"model":[9,49,131,144],"an":[10],"individual\u2019s":[11],"trait":[13,52],"from":[14,29,173],"a":[15,33,44,79,103,167],"variety":[16],"of":[17,26,71,98,136,149],"signals.":[18],"However,":[19],"few":[20],"studies":[21],"have":[22],"tackled":[23],"the":[24,50,61,64,69,72,96,99,124,137,146,150,182],"problems":[25],"integration":[27],"methodology":[28],"multiple":[30],"observations":[31],"into":[32,102],"single":[34],"prediction.":[36],"In":[37],"this":[38],"study,":[39],"we":[40,77],"focus":[41],"on":[42,63,152],"finding":[43],"novel":[45,80],"learning":[46],"architecture":[47],"under":[53],"aMany-to-Onescenario.":[54],"We":[55,140],"propose":[56],"integrate":[58,107],"not":[59],"only":[60],"information":[62],"user":[65],"but":[66],"also":[67],"consider":[68],"effect":[70],"affective":[73,114],"multimedia":[74,93,168],"stimulus.":[75],"Specifically,":[76],"present":[78],"Acoustic-Visual":[81],"Guided":[82],"Attentive":[83],"Graph":[84,125],"Convolutional":[85,126],"Network":[86,127],"for":[87,157,170,192],"enhanced":[88],"recognition.":[90,159,195],"The":[91],"emotional":[92],"content":[94],"guides":[95],"formation":[97],"physiological":[100],"responses":[101,112],"graph-like":[104],"structure":[105],"latent":[108],"inter-correlation":[109,134],"among":[110],"all":[111],"toward":[113],"multimedia.":[115],"Then":[116],"these":[117],"graphs":[118],"would":[119],"be":[120,190],"further":[121],"processed":[122],"by":[123],"(GCN)":[128],"jointly":[130],"instances":[132],"and":[133,175,181],"levels":[135],"subject\u2019s":[138],"responses.":[139],"show":[141],"that":[142,163],"our":[143],"outperforms":[145],"current":[147],"state":[148],"art":[151],"two":[153],"large":[154],"public":[155],"corpora":[156],"Further":[160],"analysis":[161],"reveals":[162],"there":[164],"indeed":[165],"exists":[166],"preference":[169],"inferring":[171],"physiology,":[174],"several":[176],"frequency-domain":[177],"descriptors":[178],"in":[179,185],"ECG":[180],"tonic":[183],"component":[184],"EDA":[186],"are":[187],"shown":[188],"robust":[191]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}