{"id":"https://openalex.org/W2805944731","doi":"https://doi.org/10.18653/v1/s18-1043","title":"TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture","display_name":"TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2805944731","doi":"https://doi.org/10.18653/v1/s18-1043","mag":"2805944731"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s18-1043","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1043","pdf_url":"https://www.aclweb.org/anthology/S18-1043.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S18-1043.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028455101","display_name":"Hardik Meisheri","orcid":"https://orcid.org/0000-0002-9014-1098"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hardik Meisheri","raw_affiliation_strings":["TCS Research New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TCS Research New Delhi, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102724695","display_name":"Lipika Dey","orcid":"https://orcid.org/0000-0003-3831-5545"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lipika Dey","raw_affiliation_strings":["TCS Research New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TCS Research New Delhi, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8084,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.93334685,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"291","last_page":"299"},"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/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"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/T12488","display_name":"Mental Health via Writing","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.9170551300048828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8448337912559509},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7560533285140991},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6791205406188965},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5905070900917053},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5673660039901733},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5551611185073853},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.47209256887435913},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43333667516708374}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9170551300048828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8448337912559509},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7560533285140991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6791205406188965},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5905070900917053},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5673660039901733},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5551611185073853},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.47209256887435913},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43333667516708374},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/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},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s18-1043","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1043","pdf_url":"https://www.aclweb.org/anthology/S18-1043.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s18-1043","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1043","pdf_url":"https://www.aclweb.org/anthology/S18-1043.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7599999904632568,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2805944731.pdf","grobid_xml":"https://content.openalex.org/works/W2805944731.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W37461795","https://openalex.org/W180870983","https://openalex.org/W1569507287","https://openalex.org/W1964613733","https://openalex.org/W2022204871","https://openalex.org/W2040467972","https://openalex.org/W2079735306","https://openalex.org/W2099813784","https://openalex.org/W2111975591","https://openalex.org/W2133564696","https://openalex.org/W2156413587","https://openalex.org/W2250539671","https://openalex.org/W2505415825","https://openalex.org/W2527467788","https://openalex.org/W2557816620","https://openalex.org/W2597655663","https://openalex.org/W2606347107","https://openalex.org/W2757162124","https://openalex.org/W2772733244","https://openalex.org/W2805744755","https://openalex.org/W2806227953","https://openalex.org/W2949709688","https://openalex.org/W2950974174","https://openalex.org/W2963223838","https://openalex.org/W2963291843","https://openalex.org/W2964308564","https://openalex.org/W4234894178"],"related_works":["https://openalex.org/W2128514324","https://openalex.org/W3186948874","https://openalex.org/W3116646283","https://openalex.org/W3114100246","https://openalex.org/W3195168932","https://openalex.org/W1996541855","https://openalex.org/W2964177319","https://openalex.org/W3082447286","https://openalex.org/W4297408405","https://openalex.org/W4287854812"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"system":[3,73],"description":[4],"of":[5,45,59,66],"our":[6],"submission":[7],"to":[8,36],"the":[9,16],"SemEval-2018":[10],"task-1:":[11],"Affect":[12],"in":[13,32,84],"tweets":[14],"for":[15],"English":[17],"language.":[18],"We":[19],"combine":[20],"three":[21],"different":[22,60,67,85],"features":[23,68],"generated":[24],"using":[25,50],"deep":[26],"learning":[27],"models":[28],"and":[29,81],"traditional":[30],"methods":[31],"support":[33],"vector":[34],"machines":[35],"create":[37],"a":[38,46,51,57],"unified":[39],"ensemble":[40],"system.":[41],"A":[42],"robust":[43],"representation":[44],"tweet":[47],"is":[48,69],"learned":[49],"multi-attention":[52],"based":[53],"architecture":[54],"which":[55],"uses":[56],"mixture":[58],"pre-trained":[61],"embeddings.":[62],"In":[63],"addition,":[64],"analysis":[65],"also":[70],"presented.":[71],"Our":[72],"ranked":[74],"2":[75],"nd":[76],",":[77,80],"5":[78],"th":[79,83],"7":[82],"subtasks":[86],"among":[87],"75":[88],"teams.":[89]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
