{"id":"https://openalex.org/W4400017403","doi":"https://doi.org/10.1108/el-05-2023-0105","title":"A robust approach for aspect-based sentiment analysis using deep learning and domain ontologies","display_name":"A robust approach for aspect-based sentiment analysis using deep learning and domain ontologies","publication_year":2024,"publication_date":"2024-06-17","ids":{"openalex":"https://openalex.org/W4400017403","doi":"https://doi.org/10.1108/el-05-2023-0105"},"language":"en","primary_location":{"id":"doi:10.1108/el-05-2023-0105","is_oa":false,"landing_page_url":"https://doi.org/10.1108/el-05-2023-0105","pdf_url":null,"source":{"id":"https://openalex.org/S902750600","display_name":"The Electronic Library","issn_l":"0264-0473","issn":["0264-0473","1758-616X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Electronic Library","raw_type":"journal-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/A5102300739","display_name":"Srishti Sharma","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Srishti Sharma","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5081883453","display_name":"Mala Saraswat","orcid":"https://orcid.org/0000-0002-6620-5098"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mala Saraswat","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102300739"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8131,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86916878,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"42","issue":"3","first_page":"498","last_page":"518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9962999820709229,"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":0.9927999973297119,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.6973599791526794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.685310959815979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5858436226844788},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5636523962020874},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5412186980247498},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48254460096359253},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09142455458641052}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6973599791526794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.685310959815979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5858436226844788},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5636523962020874},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5412186980247498},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48254460096359253},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09142455458641052},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/el-05-2023-0105","is_oa":false,"landing_page_url":"https://doi.org/10.1108/el-05-2023-0105","pdf_url":null,"source":{"id":"https://openalex.org/S902750600","display_name":"The Electronic Library","issn_l":"0264-0473","issn":["0264-0473","1758-616X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Electronic Library","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W319996907","https://openalex.org/W1540205124","https://openalex.org/W1576979497","https://openalex.org/W1614298861","https://openalex.org/W1797037330","https://openalex.org/W1967274749","https://openalex.org/W1988939740","https://openalex.org/W2019207508","https://openalex.org/W2084633738","https://openalex.org/W2111620038","https://openalex.org/W2132166724","https://openalex.org/W2144506976","https://openalex.org/W2160660844","https://openalex.org/W2164358929","https://openalex.org/W2165664073","https://openalex.org/W2187983815","https://openalex.org/W2208552932","https://openalex.org/W2250539671","https://openalex.org/W2296071000","https://openalex.org/W2407091393","https://openalex.org/W2412751481","https://openalex.org/W2465743871","https://openalex.org/W2566964269","https://openalex.org/W2766052996","https://openalex.org/W2786411768","https://openalex.org/W2793690612","https://openalex.org/W2912723748","https://openalex.org/W2921600946","https://openalex.org/W2949998441","https://openalex.org/W2998964503","https://openalex.org/W3001254509","https://openalex.org/W3036066542","https://openalex.org/W3082412894","https://openalex.org/W3101540846","https://openalex.org/W3174284607","https://openalex.org/W3216957416","https://openalex.org/W4221141436","https://openalex.org/W4232197863","https://openalex.org/W4293550597","https://openalex.org/W4310804083","https://openalex.org/W4311983224","https://openalex.org/W4312732279","https://openalex.org/W4319984444","https://openalex.org/W4378465262","https://openalex.org/W4379466622","https://openalex.org/W4380631157","https://openalex.org/W4385611483","https://openalex.org/W4390551645","https://openalex.org/W6607467106"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Purpose":[0],"The":[1,35,64,164],"purpose":[2],"of":[3,24,76,93,158,166,177,184],"this":[4],"research":[5],"study":[6,147],"is":[7,18,83,99,103,109,116,135],"to":[8,71,128],"improve":[9],"sentiment":[10,32],"analysis":[11],"(SA)":[12],"at":[13],"the":[14,73,120,175,182,185],"aspect":[15,25,54,80,121,125,134,172],"level,":[16],"which":[17],"accomplished":[19],"through":[20],"two":[21],"independent":[22],"goals":[23],"term":[26,55],"and":[27,30,40,57,79,112,131,161,174],"opinion":[28,46],"extraction":[29],"subsequent":[31],"classification.":[33,62],"Design/methodology/approach":[34],"proposed":[36,74],"architecture":[37],"uses":[38],"neighborhood":[39],"dependency":[41],"tree-based":[42],"relations":[43],"for":[44,53,61,152,170],"target":[45],"extraction,":[47,56],"a":[48,138,149],"domain\u2013ontology-based":[49],"knowledge":[50],"management":[51],"system":[52],"deep":[58,68,159,178],"learning":[59,69,160,179],"techniques":[60],"Findings":[63],"authors":[65],"use":[66,157,165,176],"different":[67],"architectures":[70],"test":[72],"approach":[75],"both":[77],"review":[78],"levels.":[81],"It":[82],"reported":[84,143],"that":[85,155],"Vanilla":[86],"recurrent":[87,107],"neural":[88,114],"network":[89,115],"has":[90],"an":[91],"accuracy":[92,183],"83.22%,":[94],"long":[95],"short-term":[96],"memory":[97],"(LSTM)":[98],"89.87%":[100],"accurate,":[101,105],"Bi-LSTM":[102],"91.57%":[104],"gated":[106],"unit":[108],"65.57%":[110],"accurate":[111],"convolutional":[113],"82.33%":[117],"accurate.":[118],"For":[119],"level":[122],"analysis,":[123],"\u03c1":[124],"comes":[126],"out":[127],"be":[129],"0.712":[130],"\u0394":[132],"2":[133],"0.384,":[136],"indicating":[137],"marked":[139],"improvement":[140],"over":[141],"previously":[142],"results.":[144],"Originality/value":[145],"This":[146],"suggests":[148],"novel":[150],"method":[151],"aspect-based":[153],"SA":[154,186],"makes":[156],"domain":[162,167],"ontologies.":[163],"ontologies":[168],"allows":[169],"enhanced":[171],"identification,":[173],"algorithms":[180],"enhances":[181],"task.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}