{"id":"https://openalex.org/W4312340905","doi":"https://doi.org/10.1109/icpr56361.2022.9956479","title":"Aspect-based Sentiment Analysis with Graph Convolutional Networks over Dependency Awareness","display_name":"Aspect-based Sentiment Analysis with Graph Convolutional Networks over Dependency Awareness","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312340905","doi":"https://doi.org/10.1109/icpr56361.2022.9956479"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956479","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956479","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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/A5100422559","display_name":"Xue Wang","orcid":"https://orcid.org/0000-0002-2381-9145"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Wang","raw_affiliation_strings":["Shandong Normal University,Shandong,China","Shandong Normal University, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Normal University,Shandong,China","institution_ids":["https://openalex.org/I28006308"]},{"raw_affiliation_string":"Shandong Normal University, Shandong, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716216","display_name":"Peiyu Liu","orcid":"https://orcid.org/0000-0002-2905-5473"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peiyu Liu","raw_affiliation_strings":["Shandong Normal University,Shandong,China","Shandong Normal University, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Normal University,Shandong,China","institution_ids":["https://openalex.org/I28006308"]},{"raw_affiliation_string":"Shandong Normal University, Shandong, China","institution_ids":["https://openalex.org/I28006308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003571051","display_name":"Zhenfang Zhu","orcid":"https://orcid.org/0000-0002-7217-3109"},"institutions":[{"id":"https://openalex.org/I4210099312","display_name":"Shandong Jiaotong University","ror":"https://ror.org/01848hk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfang Zhu","raw_affiliation_strings":["Shandong Jiaotong University,Shandong,China","Shandong Jiaotong University, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Jiaotong University,Shandong,China","institution_ids":["https://openalex.org/I4210099312"]},{"raw_affiliation_string":"Shandong Jiaotong University, Shandong, China","institution_ids":["https://openalex.org/I4210099312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079882994","display_name":"Ran Lu","orcid":"https://orcid.org/0000-0002-5160-3122"},"institutions":[{"id":"https://openalex.org/I28006308","display_name":"Shandong Normal University","ror":"https://ror.org/01wy3h363","country_code":"CN","type":"education","lineage":["https://openalex.org/I28006308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Lu","raw_affiliation_strings":["Shandong Normal University,Shandong,China","Shandong Normal University, Shandong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Normal University,Shandong,China","institution_ids":["https://openalex.org/I28006308"]},{"raw_affiliation_string":"Shandong Normal University, Shandong, China","institution_ids":["https://openalex.org/I28006308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"2238","last_page":"2245"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"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":1.0,"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":0.9977999925613403,"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":0.9968000054359436,"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/dependency","display_name":"Dependency (UML)","score":0.8261176347732544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8247921466827393},{"id":"https://openalex.org/keywords/dependency-grammar","display_name":"Dependency grammar","score":0.6801143288612366},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6086185574531555},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.5994095802307129},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5700436234474182},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.553412914276123},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.538959264755249},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5203356742858887},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43087896704673767},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.43022939562797546},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4202691614627838},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3425597548484802},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32930999994277954}],"concepts":[{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.8261176347732544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8247921466827393},{"id":"https://openalex.org/C164883195","wikidata":"https://www.wikidata.org/wiki/Q674834","display_name":"Dependency grammar","level":3,"score":0.6801143288612366},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6086185574531555},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.5994095802307129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5700436234474182},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.553412914276123},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.538959264755249},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5203356742858887},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43087896704673767},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.43022939562797546},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4202691614627838},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3425597548484802},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32930999994277954},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956479","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956479","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5400000214576721,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W193524605","https://openalex.org/W1533861849","https://openalex.org/W2113125055","https://openalex.org/W2123751690","https://openalex.org/W2147880316","https://openalex.org/W2250539671","https://openalex.org/W2251124635","https://openalex.org/W2251294039","https://openalex.org/W2251648804","https://openalex.org/W2252057809","https://openalex.org/W2296071000","https://openalex.org/W2465978385","https://openalex.org/W2529550020","https://openalex.org/W2562607067","https://openalex.org/W2788610610","https://openalex.org/W2875308690","https://openalex.org/W2891778157","https://openalex.org/W2896457183","https://openalex.org/W2949847915","https://openalex.org/W2952357537","https://openalex.org/W2955633839","https://openalex.org/W2963168371","https://openalex.org/W2963909901","https://openalex.org/W2964164368","https://openalex.org/W2970583420","https://openalex.org/W2970748008","https://openalex.org/W2971220558","https://openalex.org/W2997013919","https://openalex.org/W3035529900","https://openalex.org/W3035740499","https://openalex.org/W3100456868","https://openalex.org/W3105174597","https://openalex.org/W3106306852","https://openalex.org/W3116312348","https://openalex.org/W3116500963","https://openalex.org/W3117670243","https://openalex.org/W3118681031","https://openalex.org/W3154271556","https://openalex.org/W3167287584","https://openalex.org/W3167369375","https://openalex.org/W3173982660","https://openalex.org/W3176719207","https://openalex.org/W3185037347","https://openalex.org/W4385245566","https://openalex.org/W6607799657","https://openalex.org/W6631943919","https://openalex.org/W6676723433","https://openalex.org/W6678646961","https://openalex.org/W6682082992","https://openalex.org/W6697121895","https://openalex.org/W6727807531","https://openalex.org/W6732958910","https://openalex.org/W6739901393","https://openalex.org/W6752770541","https://openalex.org/W6755207826","https://openalex.org/W6764456104","https://openalex.org/W6799318982"],"related_works":["https://openalex.org/W2098784136","https://openalex.org/W4241489294","https://openalex.org/W63925617","https://openalex.org/W2252142543","https://openalex.org/W122365991","https://openalex.org/W2151754849","https://openalex.org/W3123290982","https://openalex.org/W2405117110","https://openalex.org/W2108975147","https://openalex.org/W4285169662"],"abstract_inverted_index":{"Aspect-based":[0],"sentiment":[1,8],"analysis":[2],"(ABSA)":[3],"aims":[4],"to":[5,34,62,65,118,136],"predict":[6],"the":[7,44,47,59,69,80,99,111,124,149],"polarities":[9],"of":[10,46,110,114,153],"specific":[11,139],"aspects":[12],"in":[13,52,94],"a":[14,85],"comment":[15],"sentence.":[16],"Nowadays,":[17],"models":[18,42],"based":[19],"on":[20,31,145],"graph":[21,89],"neural":[22],"networks":[23,91],"enhance":[24],"semantic":[25,66],"perception":[26,116],"by":[27,73],"using":[28],"dependency":[29,32,48,60,74,115],"relations":[30,54,103],"graphs":[33],"analyze":[35],"context":[36],"and":[37,55,68,107,151],"aspect":[38,140],"words.":[39,142],"However,":[40],"these":[41],"ignore":[43],"importance":[45],"type":[49],"information":[50,67,113,122],"contained":[51],"word":[53],"do":[56],"not":[57],"utilize":[58],"types":[61],"pay":[63],"attention":[64,106,135],"noise":[70],"problem":[71],"caused":[72],"tree":[75],"parsing":[76],"error.":[77],"To":[78],"solve":[79],"above":[81],"problems,":[82],"we":[83],"propose":[84],"novel":[86],"deep":[87],"dependency-aware":[88],"convolutional":[90],"(DA-GCN)":[92],"model":[93],"this":[95],"paper.":[96],"Among":[97],"them,":[98],"DA-GCN":[100],"establishes":[101],"interactive":[102],"with":[104],"multi-head":[105],"makes":[108],"use":[109],"grammar":[112],"jointly":[117],"effectively":[119],"learn":[120],"related":[121],"from":[123],"generated":[125],"graphs.":[126],"We":[127],"introduce":[128],"multiple":[129],"conditional":[130],"random":[131],"fields":[132],"fusing":[133],"structured":[134],"better":[137],"capture":[138],"opinion":[141],"Experimental":[143],"results":[144],"five":[146],"datasets":[147],"prove":[148],"effectiveness":[150],"advancement":[152],"our":[154],"proposed":[155],"model.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
