{"id":"https://openalex.org/W4403582573","doi":"https://doi.org/10.1145/3627673.3679910","title":"End-to-End Aspect Based Sentiment Analysis Using Graph Attention Network","display_name":"End-to-End Aspect Based Sentiment Analysis Using Graph Attention Network","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403582573","doi":"https://doi.org/10.1145/3627673.3679910"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","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/A5103204969","display_name":"Abir Chakraborty","orcid":"https://orcid.org/0000-0003-1796-794X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abir Chakraborty","raw_affiliation_strings":["Microsoft, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103204969"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16243289,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3663","last_page":"3668"},"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":0.9973000288009644,"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/T10028","display_name":"Topic Modeling","score":0.9950000047683716,"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":0.734375},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.7021540403366089},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47721439599990845},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4179244041442871},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3155232071876526},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2569199204444885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.734375},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.7021540403366089},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47721439599990845},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4179244041442871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3155232071876526},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2569199204444885}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627673.3679910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2251294039","https://openalex.org/W2251648804","https://openalex.org/W2296283641","https://openalex.org/W2465978385","https://openalex.org/W2562607067","https://openalex.org/W2741252866","https://openalex.org/W2756816896","https://openalex.org/W2757541972","https://openalex.org/W2767439512","https://openalex.org/W2808182015","https://openalex.org/W2896786335","https://openalex.org/W2950488390","https://openalex.org/W2963168371","https://openalex.org/W2963274454","https://openalex.org/W2964121744","https://openalex.org/W2964164368","https://openalex.org/W2964401366","https://openalex.org/W2965510113","https://openalex.org/W2969743835","https://openalex.org/W2985056549","https://openalex.org/W2998446468","https://openalex.org/W3035529900","https://openalex.org/W3098387335","https://openalex.org/W3105083537","https://openalex.org/W3120304799","https://openalex.org/W3138389337","https://openalex.org/W3202729335","https://openalex.org/W3206646281","https://openalex.org/W3207431201","https://openalex.org/W4285277253","https://openalex.org/W4385570584","https://openalex.org/W4385571465","https://openalex.org/W4385572041","https://openalex.org/W4385572650","https://openalex.org/W4385718038"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2151749779","https://openalex.org/W2548633793","https://openalex.org/W3179968364","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214"],"abstract_inverted_index":{"In":[0],"this":[1],"work":[2],"we":[3],"investigate":[4],"the":[5,36,40,53,61,70,78,82,86,108,120,128,138,148],"capability":[6],"of":[7,39,72,122],"Graph":[8,48],"Attention":[9,49],"Network":[10,50],"for":[11,151],"extracting":[12],"aspect":[13,145],"and":[14,18,55,80,94,103,131],"opinion":[15,19],"terms.":[16],"Aspect":[17],"term":[20],"extraction":[21],"is":[22,64,133],"posed":[23],"as":[24,43,146],"a":[25,47,65,73,143],"token-level":[26],"classification":[27],"task":[28],"akin":[29],"to":[30,107,136],"named":[31],"entity":[32],"recognition.":[33],"We":[34,58,96,111],"use":[35],"dependency":[37,62,139],"tree":[38,140],"input":[41],"query":[42,130],"additional":[44,99],"feature":[45,67],"in":[46,69,105,119,127],"along":[51],"with":[52,98],"token":[54],"part-of-speech":[56],"features.":[57],"show":[59,113],"that":[60,68,114],"structure":[63],"powerful":[66],"presence":[71,121],"CRF":[74,109],"layer":[75],"substantially":[76],"improves":[77],"performance":[79],"generates":[81],"best":[83],"result":[84],"on":[85,142],"commonly":[87],"used":[88],"datasets":[89],"from":[90],"SemEval":[91],"2014,":[92],"2015":[93],"2016.":[95],"experiment":[97],"layers":[100],"like":[101],"BiLSTM":[102],"Transformer":[104],"addition":[106],"layer.":[110],"also":[112],"our":[115],"approach":[116],"works":[117],"well":[118],"multiple":[123],"aspects":[124],"or":[125],"sentiments":[126],"same":[129],"it":[132],"not":[134],"necessary":[135],"modify":[137],"based":[141],"single":[144],"was":[147],"original":[149],"application":[150],"sentiment":[152],"classification.":[153]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}