{"id":"https://openalex.org/W4214875575","doi":"https://doi.org/10.1109/tkde.2022.3155290","title":"Multi-level Attention Map Network for Multimodal Sentiment Analysis","display_name":"Multi-level Attention Map Network for Multimodal Sentiment Analysis","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4214875575","doi":"https://doi.org/10.1109/tkde.2022.3155290"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3155290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3155290","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5078813301","display_name":"Xiaojun Xue","orcid":"https://orcid.org/0000-0002-1925-9202"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaojun Xue","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, 47833 Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, 47833 Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100749940","display_name":"Chunxia Zhang","orcid":"https://orcid.org/0000-0003-0897-7986"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxia Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, 47833 Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, 47833 Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082774439","display_name":"Zhendong Niu","orcid":"https://orcid.org/0000-0002-0576-7572"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhendong Niu","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, 47833 Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, 47833 Beijing, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080738591","display_name":"Xindong Wu","orcid":"https://orcid.org/0000-0003-2396-1704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xindong Wu","raw_affiliation_strings":["Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology, Hefei, Anhui 230009, China","Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei, Anhui 230026, China, and also with the Mininglamp Academy of Sciences, Minininglamp, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology, Hefei, Anhui 230009, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering with Big Data, Ministry of Education, Hefei University of Technology, Hefei, Anhui 230026, China, and also with the Mininglamp Academy of Sciences, Minininglamp, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5078813301"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":9.0298,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.9817867,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994000196456909,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994000196456909,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.978600025177002,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8398236036300659},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.8233597278594971},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.572704553604126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5543672442436218},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5345315933227539},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4855220317840576},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.48288726806640625},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4824391305446625},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4567067325115204},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45407024025917053},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4528272747993469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39612382650375366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3533111810684204},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.22125226259231567},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0848684310913086}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8398236036300659},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8233597278594971},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.572704553604126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5543672442436218},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5345315933227539},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4855220317840576},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.48288726806640625},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4824391305446625},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4567067325115204},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45407024025917053},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4528272747993469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39612382650375366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3533111810684204},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.22125226259231567},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0848684310913086},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3155290","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3155290","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4557345371","display_name":null,"funder_award_id":"62072039","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1832693441","https://openalex.org/W2064675550","https://openalex.org/W2075456404","https://openalex.org/W2166015963","https://openalex.org/W2250539671","https://openalex.org/W2265228180","https://openalex.org/W2290551858","https://openalex.org/W2295739661","https://openalex.org/W2313683095","https://openalex.org/W2341680599","https://openalex.org/W2407348013","https://openalex.org/W2472490454","https://openalex.org/W2551829638","https://openalex.org/W2562607067","https://openalex.org/W2744979708","https://openalex.org/W2747623286","https://openalex.org/W2757541972","https://openalex.org/W2767484504","https://openalex.org/W2787293089","https://openalex.org/W2798802604","https://openalex.org/W2883409523","https://openalex.org/W2894676449","https://openalex.org/W2896457183","https://openalex.org/W2899197626","https://openalex.org/W2905551935","https://openalex.org/W2915977493","https://openalex.org/W2956959730","https://openalex.org/W2963168371","https://openalex.org/W2964010806","https://openalex.org/W2964164368","https://openalex.org/W2997573100","https://openalex.org/W3015558147","https://openalex.org/W3035177206","https://openalex.org/W3045969489","https://openalex.org/W3095024162","https://openalex.org/W3104739527","https://openalex.org/W3112718522","https://openalex.org/W3124962741","https://openalex.org/W3128412859","https://openalex.org/W3147461355","https://openalex.org/W3173744006","https://openalex.org/W3190316647","https://openalex.org/W3214432797","https://openalex.org/W4239946314","https://openalex.org/W4246193833","https://openalex.org/W6607799657","https://openalex.org/W6637373629","https://openalex.org/W6676867598","https://openalex.org/W6679792166","https://openalex.org/W6729014267","https://openalex.org/W6752083267"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4382701072","https://openalex.org/W4256502920"],"abstract_inverted_index":{"Multimodal":[0],"sentiment":[1,90],"analysis":[2],"(MSA)":[3],"is":[4,94,116,129,149,178],"a":[5,66],"very":[6],"challenging":[7],"task":[8],"due":[9],"to":[10,72,118,131,151,181],"its":[11,187],"complex":[12],"and":[13,32,52,78,82,108,134,185,194],"complementary":[14],"interactions":[15,155],"between":[16],"multiple":[17,54],"modalities,":[18],"which":[19,47],"can":[20],"be":[21],"widely":[22],"applied":[23],"into":[24],"areas":[25],"of":[26,96,192],"product":[27],"marketing,":[28],"public":[29,172],"opinion":[30],"monitoring,":[31],"so":[33],"on.":[34],"However,":[35],"previous":[36],"works":[37],"directly":[38],"utilized":[39],"the":[40,48,80,136,146,154,161,175,182],"features":[41,87,122,141],"extracted":[42],"from":[43,123],"multimodal":[44,61,76,89,124,143],"data,":[45],"in":[46],"noise":[49,74,133],"reduction":[50],"within":[51],"among":[53,85,156],"modalities":[55],"has":[56],"been":[57],"largely":[58],"ignored":[59],"before":[60,75,142],"fusion.":[62,144],"This":[63],"paper":[64],"proposes":[65],"multi-level":[67,103,157],"attention":[68,104,109,158],"map":[69,105,110],"network":[70],"(MAMN)":[71],"filter":[73,132],"fusion":[77,111,165],"capture":[79],"consistent":[81],"heterogeneous":[83],"correlations":[84],"multi-granularity":[86,99,121,140],"for":[88,139],"analysis.":[91],"Architecturally,":[92],"MAMN":[93],"comprised":[95],"three":[97,171],"modules:":[98],"feature":[100],"extraction":[101],"module,":[102,107],"generation":[106],"module.":[112],"The":[113,126],"first":[114],"module":[115,128,148],"designed":[117],"sufficiently":[119],"extract":[120],"data.":[125],"second":[127],"constructed":[130],"enhance":[135],"representation":[137],"ability":[138],"And":[145],"third":[147],"built":[150],"extensibly":[152],"mine":[153],"maps":[159],"by":[160],"proposed":[162,176],"extensible":[163],"co-attention":[164],"method.":[166],"Extensive":[167],"experimental":[168],"results":[169],"on":[170,189],"datasets":[173],"show":[174],"model":[177],"significantly":[179],"superior":[180],"state-of-the-art":[183],"methods,":[184],"demonstrate":[186],"effectiveness":[188],"two":[190],"tasks":[191],"document-based":[193],"aspect-based":[195],"MSA":[196],"tasks.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}