{"id":"https://openalex.org/W3200465303","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533506","title":"Aspect-Based Sentiment Classification with Background Information and Syntactic Auxiliary Tasks","display_name":"Aspect-Based Sentiment Classification with Background Information and Syntactic Auxiliary Tasks","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200465303","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533506","mag":"3200465303"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5075559684","display_name":"Ming-Fan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Fan Li","raw_affiliation_strings":["Ping An Life Insurance of China, Ltd.,Shenzhen,China","Ping An Life Insurance of China, Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210136318"]},{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018361371","display_name":"Kaijie Zhou","orcid":"https://orcid.org/0009-0003-5041-9977"},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaijie Zhou","raw_affiliation_strings":["Ping An Life Insurance of China, Ltd.,Shenzhen,China","Ping An Life Insurance of China, Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210136318"]},{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4401726822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108104518","display_name":"Xuan Li","orcid":"https://orcid.org/0009-0003-0815-3845"},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuan Li","raw_affiliation_strings":["Ping An Life Insurance of China, Ltd.,Shenzhen,China","Ping An Life Insurance of China, Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210136318"]},{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4401726822"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108756348","display_name":"Jianping Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136318","display_name":"New York Life Insurance Company (United States)","ror":"https://ror.org/03a4nen96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210136318"]},{"id":"https://openalex.org/I4401726822","display_name":"Ping An (China)","ror":"https://ror.org/004yv2z91","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726822"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianping Shen","raw_affiliation_strings":["Ping An Life Insurance of China, Ltd.,Shenzhen,China","Ping An Life Insurance of China, Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd.,Shenzhen,China","institution_ids":["https://openalex.org/I4210136318"]},{"raw_affiliation_string":"Ping An Life Insurance of China, Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4401726822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1465,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39822196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9973000288009644,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9965999722480774,"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":0.8619565367698669},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7545007467269897},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7278364300727844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6831670999526978},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.6189428567886353},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6062828898429871},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6034430861473083},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5662778615951538},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5398113131523132},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5164270997047424},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4392826557159424},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4062540829181671}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8619565367698669},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7545007467269897},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7278364300727844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6831670999526978},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6189428567886353},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6062828898429871},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6034430861473083},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5662778615951538},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5398113131523132},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5164270997047424},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4392826557159424},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4062540829181671},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2130549755","https://openalex.org/W2165855670","https://openalex.org/W2250539671","https://openalex.org/W2251294039","https://openalex.org/W2251648804","https://openalex.org/W2252057809","https://openalex.org/W2567698949","https://openalex.org/W2624871570","https://openalex.org/W2753709519","https://openalex.org/W2787648855","https://openalex.org/W2788610610","https://openalex.org/W2885786899","https://openalex.org/W2953008521","https://openalex.org/W2955633839","https://openalex.org/W2963168371","https://openalex.org/W2963240575","https://openalex.org/W2963909901","https://openalex.org/W2964164368","https://openalex.org/W2964401366","https://openalex.org/W2971220558","https://openalex.org/W3010575424","https://openalex.org/W3016975783","https://openalex.org/W3083435909","https://openalex.org/W3094807849","https://openalex.org/W4287728517","https://openalex.org/W6739365718","https://openalex.org/W6748407919","https://openalex.org/W6748540291","https://openalex.org/W6771972468","https://openalex.org/W6774843077","https://openalex.org/W6779824286","https://openalex.org/W6780226713","https://openalex.org/W6784769054"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2754876402"],"abstract_inverted_index":{"Aspect-based":[0],"sentiment":[1,9,83],"classification":[2,84],"is":[3,95],"the":[4,8,48,56,77,81,98],"task":[5,22],"of":[6,11,55],"predicting":[7],"tendency":[10],"a":[12,15,32],"text":[13],"toward":[14],"given":[16,57],"aspect.":[17],"Existing":[18],"works":[19],"on":[20,25,87],"this":[21],"mainly":[23],"focus":[24],"aspect-relevant":[26],"information.":[27],"In":[28],"contrast,":[29],"we":[30,59],"design":[31],"model":[33,50,78,100],"(BAT)":[34],"which":[35],"could":[36],"extract":[37],"overall":[38],"Background":[39],"information":[40],"as":[41,43],"well":[42],"Aspect-relevant":[44],"informaTion.":[45],"To":[46],"make":[47],"BAT":[49],"learn":[51],"better":[52],"semantic":[53],"representation":[54],"text,":[58],"introduce":[60],"two":[61],"auxiliary":[62,71],"tasks":[63,72],"(dependency":[64],"neighborhood":[65],"prediction":[66],"and":[67,97],"part-of-speech":[68],"tagging).":[69],"These":[70],"are":[73],"used":[74],"to":[75],"train":[76],"together":[79],"with":[80],"main":[82],"task.":[85],"Experiments":[86],"three":[88],"benchmark":[89],"datasets":[90],"demonstrate":[91],"that":[92],"our":[93],"method":[94],"effective":[96],"proposed":[99],"achieves":[101],"substantial":[102],"performance":[103],"improvements":[104],"over":[105],"comparison":[106],"models.":[107]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
