{"id":"https://openalex.org/W3015468019","doi":"https://doi.org/10.7488/era/267","title":"Multi-view representation learning for natural language processing applications","display_name":"Multi-view representation learning for natural language processing applications","publication_year":2020,"publication_date":"2020-04-08","ids":{"openalex":"https://openalex.org/W3015468019","doi":"https://doi.org/10.7488/era/267","mag":"3015468019"},"language":"en","primary_location":{"id":"pmh:oai:era.ed.ac.uk:1842/36966","is_oa":true,"landing_page_url":"https://hdl.handle.net/1842/36966","pdf_url":"https://hdl.handle.net/1842/36966","source":{"id":"https://openalex.org/S7407055182","display_name":"ERA","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis or Dissertation"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/1842/36966","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033964678","display_name":"Nikolaos Papasarantopoulos","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Papasarantopoulos, Nikolaos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5033964678"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.5960999727249146,"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/T12031","display_name":"Speech and dialogue systems","score":0.5960999727249146,"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":0.5751821398735046},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.558714747428894},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5256646275520325},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.5033828616142273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48201242089271545},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.3358386754989624},{"id":"https://openalex.org/keywords/cognitive-science","display_name":"Cognitive science","score":0.32038840651512146},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.19382092356681824},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11960217356681824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5751821398735046},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.558714747428894},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5256646275520325},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.5033828616142273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48201242089271545},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3358386754989624},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.32038840651512146},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.19382092356681824},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11960217356681824},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:era.ed.ac.uk:1842/36966","is_oa":true,"landing_page_url":"https://hdl.handle.net/1842/36966","pdf_url":"https://hdl.handle.net/1842/36966","source":{"id":"https://openalex.org/S7407055182","display_name":"ERA","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis or Dissertation"},{"id":"doi:10.7488/era/267","is_oa":true,"landing_page_url":"https://doi.org/10.7488/era/267","pdf_url":null,"source":{"id":"https://openalex.org/S7407050748","display_name":"University of Edinburgh","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null},{"id":"mag:3015468019","is_oa":false,"landing_page_url":"https://era.ed.ac.uk/handle/1842/36966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:era.ed.ac.uk:1842/36966","is_oa":true,"landing_page_url":"https://hdl.handle.net/1842/36966","pdf_url":"https://hdl.handle.net/1842/36966","source":{"id":"https://openalex.org/S7407055182","display_name":"ERA","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis or Dissertation"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3015468019.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3038445625","https://openalex.org/W2508801293","https://openalex.org/W10714513","https://openalex.org/W2295146128","https://openalex.org/W2884001105","https://openalex.org/W1576817641","https://openalex.org/W2515884433","https://openalex.org/W3006542816","https://openalex.org/W2904308181","https://openalex.org/W2139123573","https://openalex.org/W3040357889","https://openalex.org/W2805389232","https://openalex.org/W2762930019","https://openalex.org/W2017338566","https://openalex.org/W152208608","https://openalex.org/W3015419376","https://openalex.org/W1803549767","https://openalex.org/W2163004744","https://openalex.org/W65813402","https://openalex.org/W2911921634"],"abstract_inverted_index":{"The":[0,73,384],"pervasion":[1],"of":[2,9,22,31,68,75,84,92,112,143,156,169,197,212,219,273,276,292,296,334,346,387,408,417],"machine":[3,179],"learning":[4,163,180,200,299,398],"in":[5,37,82,140,152,161,205],"a":[6,99,126,186,209,239,270,274,310,326,344,365,444],"vast":[7],"number":[8],"applications":[10,262,350],"has":[11,182,202],"given":[12],"rise":[13],"to":[14,103,117,174,185,282,288,352,393,435,447],"an":[15],"increasing":[16],"demand":[17],"for":[18,79,178,330,349,424,439],"the":[19,109,141,162,167,206,217,221,250,290,293,331,377,388,404,409,415,448],"effective":[20],"processing":[21],"complex,":[23],"diverse":[24],"and":[25,147,171,268,315,356,380,406,429],"variable":[26],"datasets.":[27],"One":[28],"representative":[29],"case":[30,142],"data":[32,65],"diversity":[33],"can":[34,137],"be":[35],"found":[36],"multi-view":[38,76,198,271,297,311,327,347,396,418],"datasets,":[39,63],"which":[40],"contain":[41],"input":[42],"originating":[43],"from":[44,95,122,265,278,370],"more":[45,259,338],"than":[46],"one":[47],"source":[48],"or":[49,53,131,234],"having":[50],"multiple":[51,192],"aspects":[52],"facets.":[54],"Examples":[55],"include,":[56],"but":[57],"are":[58,229,317,433],"not":[59],"restricted":[60],"to,":[61],"multimodal":[62,251,340],"where":[64,313],"may":[66,150],"consist":[67],"audio,":[69],"image":[70,335],"and/or":[71],"text.":[72],"nature":[74],"datasets":[77,233],"calls":[78],"special":[80],"treatment":[81],"terms":[83],"representation.":[85],"A":[86,195],"subsequent":[87],"fundamental":[88],"problem":[89,100,312,333],"is":[90,115,246,390],"that":[91,190,258,373,431],"combining":[93],"information":[94,437],"potentially":[96],"incoherent":[97],"sources;":[98],"commonly":[101],"referred":[102],"as":[104,309],"view":[105,158,193],"fusion.":[106],"Quite":[107],"often,":[108],"heuristic":[110],"solution":[111],"early":[113,135,449],"fusion":[114,136,450],"applied":[116],"this":[118],"problem:":[119],"aggregating":[120],"representations":[121,177,267],"different":[123],"views":[124],"using":[125],"simple":[127],"function":[128],"(concatenation,":[129],"summation":[130],"mean":[132],"pooling).":[133],"However,":[134],"cause":[138],"overfitting":[139],"small":[144],"training":[145],"samples":[146],"also,":[148],"it":[149,308],"result":[151],"specific":[153],"statistical":[154],"properties":[155],"each":[157],"being":[159,214,443],"lost":[160],"process.":[164],"Representation":[165],"learning,":[166],"set":[168,345],"ideas":[170],"algorithms":[172],"devised":[173],"learn":[175],"meaningful":[176],"problems,":[181,441],"recently":[183],"grown":[184],"vibrant":[187],"research":[188],"field,":[189],"encompasses":[191],"setups.":[194],"plethora":[196],"representation":[199,298,397],"methods":[201],"been":[203],"proposed":[204],"literature,":[207],"with":[208,304],"large":[210],"portion":[211],"them":[213],"based":[215],"on":[216,231,376],"idea":[218],"maximising":[220],"correlation":[222],"between":[223],"available":[224],"views.":[225,322],"Commonly,":[226],"such":[227,266],"techniques":[228],"evaluated":[230],"synthetic":[232],"strictly":[235],"defined":[236],"benchmark":[237],"setups;":[238],"role":[240],"that,":[241,391],"within":[242],"Natural":[243,410,425],"Language":[244,411,426],"Processing,":[245],"often":[247],"assumed":[248],"by":[249,403],"sentiment":[252],"analysis":[253],"problem.":[254],"This":[255],"thesis":[256,389],"argues":[257],"complex":[260,440],"downstream":[261],"could":[263],"benefit":[264],"describes":[269],"contemplation":[272],"range":[275],"tasks,":[277],"static,":[279],"two-view,":[280],"unimodal":[281],"dynamic,":[283],"three-view,":[284],"trimodal":[285],"applications.setting":[286],"out":[287],"explore":[289],"limits":[291,416],"seeming":[294],"applicability":[295],"More":[300],"specifically,":[301],"we":[302,324,342,361,420],"experiment":[303],"document":[305],"summarisation,":[306],"framing":[307],"documents":[314],"summaries":[316],"considered":[318],"two":[319],"separate,":[320],"textual":[321],"Moreover,":[323],"present":[325],"inference":[328,375],"algorithm":[329],"bimodal":[332],"captioning.":[336],"Delving":[337],"into":[339],"setups,":[341],"develop":[343],"models":[348],"pertaining":[351],"videos,":[353,372],"including":[354],"tagging":[355],"text":[357,367],"generation":[358,368],"tasks.":[359],"Finally,":[360],"introduce":[362],"narration":[363],"generation,":[364],"new":[366],"task":[369],"movie":[371],"requires":[374],"storyline":[378],"level":[379],"temporal":[381],"context-based":[382],"reasoning.":[383],"main":[385],"argument":[386],"due":[392],"their":[394,422],"performance,":[395],"tools":[399],"warrant":[400],"serious":[401],"consideration":[402],"researchers":[405],"practitioners":[407],"Processing":[412,427],"community.":[413],"Exploring":[414],"representations,":[419],"investigate":[421],"fitness":[423],"tasks":[428],"show":[430],"they":[432],"able":[434],"hold":[436],"required":[438],"while":[442],"good":[445],"alternative":[446],"paradigm.":[451]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}