{"id":"https://openalex.org/W4384890998","doi":"https://doi.org/10.1145/3539618.3592060","title":"Simple Approach for Aspect Sentiment Triplet Extraction Using Span-Based Segment Tagging and Dual Extractors","display_name":"Simple Approach for Aspect Sentiment Triplet Extraction Using Span-Based Segment Tagging and Dual Extractors","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384890998","doi":"https://doi.org/10.1145/3539618.3592060"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3592060","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3592060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5092503994","display_name":"Dongxu Li","orcid":"https://orcid.org/0000-0003-2016-2675"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxu Li","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2016-2675","affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhihao Yang","orcid":"https://orcid.org/0009-0001-4989-1110"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Yang","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-4989-1110","affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013205155","display_name":"Yuquan Lan","orcid":"https://orcid.org/0009-0004-6525-2935"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuquan Lan","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-6525-2935","affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683918","display_name":"Yunqi Zhang","orcid":"https://orcid.org/0009-0003-7112-8722"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunqi Zhang","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0003-7112-8722","affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Zhao","orcid":"https://orcid.org/0000-0002-8681-5539"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zhao","raw_affiliation_strings":["Shanghai Key Laboratory of Trustworthy Computing, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8681-5539","affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Trustworthy Computing, Shanghai, China","institution_ids":["https://openalex.org/I4210139618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102868812","display_name":"Gang Zhao","orcid":"https://orcid.org/0009-0001-1349-3604"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Zhao","raw_affiliation_strings":["Microsoft, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-1349-3604","affiliations":[{"raw_affiliation_string":"Microsoft, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2374","last_page":"2378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994000196456909,"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/T10028","display_name":"Topic Modeling","score":0.9966999888420105,"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":0.8447905778884888},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.7035723328590393},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6925950646400452},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6382752656936646},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6284211874008179},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5907574892044067},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5070106983184814},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4846811592578888},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.4791911840438843},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4779760539531708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46229618787765503},{"id":"https://openalex.org/keywords/span","display_name":"Span (engineering)","score":0.4378056526184082},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38390791416168213},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.36456966400146484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34202665090560913},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3416382670402527},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1182982325553894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8447905778884888},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.7035723328590393},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6925950646400452},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6382752656936646},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6284211874008179},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5907574892044067},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5070106983184814},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4846811592578888},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.4791911840438843},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4779760539531708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46229618787765503},{"id":"https://openalex.org/C2778753569","wikidata":"https://www.wikidata.org/wiki/Q1960395","display_name":"Span (engineering)","level":2,"score":0.4378056526184082},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38390791416168213},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36456966400146484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34202665090560913},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3416382670402527},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1182982325553894},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539618.3592060","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3592060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322370","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2251648804","https://openalex.org/W2963351448","https://openalex.org/W2981852735","https://openalex.org/W3176690085","https://openalex.org/W4288089799","https://openalex.org/W4385567203"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3089396779","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W2941935829","https://openalex.org/W3013279174","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989","https://openalex.org/W4317653575"],"abstract_inverted_index":{"Aspect":[0],"sentiment":[1,15,67,123],"triplet":[2],"extraction":[3,124],"(ASTE)":[4],"is":[5,100],"a":[6,76],"task":[7],"which":[8],"extracts":[9],"aspect":[10],"terms,":[11,13],"opinion":[12],"and":[14,60,109],"polarities":[16,32],"as":[17],"triplets":[18],"from":[19,36],"review":[20],"sentences.":[21],"Existing":[22],"approaches":[23],"have":[24],"developed":[25],"bidirectional":[26,48,94],"structures":[27],"for":[28],"term":[29,128],"interaction.":[30],"Sentiment":[31],"are":[33,118],"subsequently":[34],"extracted":[35],"aspect-opinion":[37],"pairs.":[38],"These":[39],"solutions":[40],"suffer":[41],"from:":[42],"1)":[43],"high":[44],"dependency":[45],"on":[46,134],"custom":[47],"structures,":[49],"2)":[50],"inadequate":[51],"representation":[52],"of":[53,64,107,126],"the":[54,71,122,127],"information":[55,112],"through":[56,113],"existing":[57],"tagging":[58,98],"schemes,":[59],"3)":[61],"insufficient":[62],"usage":[63],"all":[65,104],"available":[66],"data.":[68],"To":[69],"address":[70],"above":[72],"issues,":[73],"we":[74],"propose":[75],"simple":[77,144],"span-based":[78],"solution":[79],"named":[80],"SimSTAR":[81,88],"with":[82],"Segment":[83],"Tagging":[84],"And":[85],"dual":[86],"extRactors.":[87],"does":[89],"not":[90],"introduce":[91],"any":[92],"additional":[93],"mechanism.":[95],"The":[96,138],"segment":[97],"scheme":[99],"capable":[101],"to":[102,120],"indicate":[103],"possible":[105],"cases":[106],"spans":[108],"reveals":[110],"more":[111],"negative":[114],"labels.":[115],"Dual":[116],"extractors":[117],"employed":[119],"make":[121],"independent":[125],"extraction.":[129],"We":[130],"evaluate":[131],"our":[132,143],"model":[133],"four":[135],"ASTE":[136],"datasets.":[137],"experimental":[139],"results":[140],"show":[141],"that":[142],"method":[145],"achieves":[146],"state-of-the-art":[147],"performance.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}