{"id":"https://openalex.org/W3007884796","doi":"https://doi.org/10.1109/bigdata47090.2019.9006119","title":"End-to-End Joint Opinion Role Labeling with BERT","display_name":"End-to-End Joint Opinion Role Labeling with BERT","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007884796","doi":"https://doi.org/10.1109/bigdata47090.2019.9006119","mag":"3007884796"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5082147952","display_name":"Wei Quan","orcid":"https://orcid.org/0000-0002-0934-8324"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Quan","raw_affiliation_strings":["College of Computing and Informatics, Drexel University Philadelphia, PA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing and Informatics, Drexel University Philadelphia, PA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796857","display_name":"Jinli Zhang","orcid":"https://orcid.org/0000-0002-5885-2519"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinli Zhang","raw_affiliation_strings":["Faculty of Information Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101569679","display_name":"Xiaohua Hu","orcid":"https://orcid.org/0000-0002-4777-3022"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaohua Tony Hu","raw_affiliation_strings":["College of Computing and Informatics, Drexel University Philadelphia, PA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing and Informatics, Drexel University Philadelphia, PA","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2438","last_page":"2446"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9972000122070312,"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":0.7959133386611938},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.7571790814399719},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6987648010253906},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.6113178133964539},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6066231727600098},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5551024675369263},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5439164638519287},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.46515899896621704},{"id":"https://openalex.org/keywords/expert-opinion","display_name":"Expert opinion","score":0.44436556100845337},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.42859071493148804},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41988953948020935},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4146023094654083},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07357749342918396}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7959133386611938},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7571790814399719},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6987648010253906},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.6113178133964539},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6066231727600098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5551024675369263},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5439164638519287},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.46515899896621704},{"id":"https://openalex.org/C3020580240","wikidata":"https://www.wikidata.org/wiki/Q663272","display_name":"Expert opinion","level":2,"score":0.44436556100845337},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.42859071493148804},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41988953948020935},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4146023094654083},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07357749342918396},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W131863957","https://openalex.org/W179875071","https://openalex.org/W182831726","https://openalex.org/W1549026077","https://openalex.org/W1608050331","https://openalex.org/W1973724169","https://openalex.org/W1978620866","https://openalex.org/W2009410854","https://openalex.org/W2011450768","https://openalex.org/W2014902591","https://openalex.org/W2052474702","https://openalex.org/W2059569661","https://openalex.org/W2088198454","https://openalex.org/W2097726431","https://openalex.org/W2099120987","https://openalex.org/W2115792525","https://openalex.org/W2115834228","https://openalex.org/W2120626200","https://openalex.org/W2147880316","https://openalex.org/W2149167588","https://openalex.org/W2151170651","https://openalex.org/W2153579005","https://openalex.org/W2158847908","https://openalex.org/W2166391512","https://openalex.org/W2250539671","https://openalex.org/W2251599843","https://openalex.org/W2251939518","https://openalex.org/W2253519362","https://openalex.org/W2511598956","https://openalex.org/W2742947407","https://openalex.org/W2790250716","https://openalex.org/W2913685946","https://openalex.org/W2963341956","https://openalex.org/W2963888891","https://openalex.org/W4205184193","https://openalex.org/W4213168938","https://openalex.org/W4294170691","https://openalex.org/W6605265046","https://openalex.org/W6607333740","https://openalex.org/W6636474999","https://openalex.org/W6677665046","https://openalex.org/W6682691769","https://openalex.org/W6691459498","https://openalex.org/W6742102919"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2093471820","https://openalex.org/W2347460059","https://openalex.org/W50079190","https://openalex.org/W2111726165","https://openalex.org/W3136048405","https://openalex.org/W182104056","https://openalex.org/W3143595119"],"abstract_inverted_index":{"Opinion":[0,15],"mining":[1,152],"has":[2,64],"raised":[3],"growing":[4],"interest":[5],"both":[6],"in":[7,11,54,83,139],"industry":[8],"and":[9,26,47,95,108,154],"academia":[10],"the":[12,33,133,146],"past":[13],"decade.":[14],"role":[16],"labeling":[17],"(ORL)":[18],"is":[19],"a":[20,69],"task":[21],"to":[22,31,100,135,145],"extract":[23,102],"opinion":[24,103,106,151],"holder":[25,107],"target":[27],"from":[28,61],"natural":[29,72],"language":[30,73],"answer":[32],"question":[34],"\u201cwho":[35],"express":[36],"what\u201d.":[37],"Recent":[38],"years,":[39],"neural":[40],"network":[41],"based":[42,80],"methods":[43,153],"with":[44],"additional":[45],"lexical":[46],"syntactic":[48,122],"features":[49],"have":[50],"achieved":[51],"state-of-the-art":[52,149],"performances":[53,67],"similar":[55],"tasks.":[56,76],"Moreover,":[57],"Bidirectional":[58,90],"Encoder":[59],"Representations":[60],"Transformers":[62],"(BERT)":[63],"shown":[65],"impressive":[66],"among":[68,132],"variety":[70],"of":[71,148],"processing":[74],"(NLP)":[75],"To":[77,126],"investigate":[78],"BERT":[79,138],"end-to-end":[81],"model":[82],"ORL,":[84],"we":[85,130],"propose":[86],"models":[87,115],"using":[88,120],"BERT,":[89],"Long":[91],"short-term":[92],"Memory":[93],"(BiLSTM)":[94],"Conditional":[96],"Random":[97],"Field":[98],"(CRF)":[99],"jointly":[101],"roles":[104],"(e.g.,":[105],"target).":[109],"Experimental":[110],"results":[111],"show":[112],"that":[113],"our":[114,127],"achieve":[116],"remarkable":[117],"scores":[118],"without":[119],"extra":[121],"and/or":[123],"semantic":[124],"features.":[125],"best":[128],"knowledge,":[129],"are":[131],"pioneers":[134],"successfully":[136],"integrate":[137],"this":[140],"manner.":[141],"Our":[142],"work":[143],"contributes":[144],"improvement":[147],"aspect-level":[150],"providing":[155],"strong":[156],"baselines":[157],"for":[158],"future":[159],"work.":[160]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
