{"id":"https://openalex.org/W4224981150","doi":"https://doi.org/10.1109/icassp43922.2022.9747192","title":"A Robust Contrastive Alignment Method for Multi-Domain Text Classification","display_name":"A Robust Contrastive Alignment Method for Multi-Domain Text Classification","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224981150","doi":"https://doi.org/10.1109/icassp43922.2022.9747192"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747192","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100400525","display_name":"Xuefeng Li","orcid":"https://orcid.org/0000-0001-7588-7716"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuefeng Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hao Lei","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Lei","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064214995","display_name":"Liwen Wang","orcid":"https://orcid.org/0009-0002-7885-8958"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liwen Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008320336","display_name":"Guanting Dong","orcid":"https://orcid.org/0000-0002-2318-0281"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanting Dong","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057816329","display_name":"Jinzheng Zhao","orcid":"https://orcid.org/0009-0004-3910-850X"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jinzheng Zhao","raw_affiliation_strings":["University of Surrey,School of Computer Science and Electronic Engineering,UK","School of Computer Science and Electronic Engineering, University of Surrey, UK"],"affiliations":[{"raw_affiliation_string":"University of Surrey,School of Computer Science and Electronic Engineering,UK","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"School of Computer Science and Electronic Engineering, University of Surrey, UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019606204","display_name":"Jiachi Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachi Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001956210","display_name":"Weiran Xu","orcid":"https://orcid.org/0000-0002-7988-080X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiran Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101679256","display_name":"Chunyun Zhang","orcid":"https://orcid.org/0000-0002-3156-754X"},"institutions":[{"id":"https://openalex.org/I59483232","display_name":"Shandong University of Finance and Economics","ror":"https://ror.org/02e2nnq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I59483232"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyun Zhang","raw_affiliation_strings":["Shandong University of Finance and Economics,Jinan,China","Shandong University of Finance and Economics, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong University of Finance and Economics,Jinan,China","institution_ids":["https://openalex.org/I59483232"]},{"raw_affiliation_string":"Shandong University of Finance and Economics, Jinan, China","institution_ids":["https://openalex.org/I59483232"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100400525"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.626,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66226815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"7827","last_page":"7831"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9987999796867371,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987999796867371,"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":0.9952999949455261,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9890000224113464,"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":0.8369147777557373},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6629756689071655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6541256904602051},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6328668594360352},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5735188722610474},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49837160110473633},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4867713451385498},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4515603184700012},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41407281160354614},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38061368465423584},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08399102091789246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8369147777557373},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6629756689071655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6541256904602051},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6328668594360352},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5735188722610474},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49837160110473633},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4867713451385498},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4515603184700012},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41407281160354614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38061368465423584},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08399102091789246},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747192","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":24,"referenced_works":["https://openalex.org/W2154359981","https://openalex.org/W2163302275","https://openalex.org/W2248051232","https://openalex.org/W2896457183","https://openalex.org/W2962897020","https://openalex.org/W2963424663","https://openalex.org/W2977981067","https://openalex.org/W2997420347","https://openalex.org/W3104002368","https://openalex.org/W3132253205","https://openalex.org/W3163658745","https://openalex.org/W3168770756","https://openalex.org/W3171676064","https://openalex.org/W3177225470","https://openalex.org/W3178103610","https://openalex.org/W3203903618","https://openalex.org/W4287812705","https://openalex.org/W6682839988","https://openalex.org/W6684149856","https://openalex.org/W6755207826","https://openalex.org/W6776700526","https://openalex.org/W6790852254","https://openalex.org/W6796703666","https://openalex.org/W6798028545"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W3155418658","https://openalex.org/W4243199227","https://openalex.org/W2379948177","https://openalex.org/W2334580170"],"abstract_inverted_index":{"Multi-domain":[0],"text":[1,34,89,117],"classification":[2,90],"can":[3],"automatically":[4],"classify":[5],"texts":[6,17],"in":[7,22,63,95,142],"various":[8,93],"scenarios.":[9],"Due":[10],"to":[11,31,58,87,114],"the":[12,19,32,40,96,134,139],"diversity":[13],"of":[14,92],"human":[15],"languages,":[16],"with":[18,129],"same":[20,97],"label":[21],"different":[23],"domains":[24,73,94],"may":[25],"differ":[26],"greatly,":[27],"which":[28,137],"brings":[29],"challenges":[30],"multi-domain":[33,116],"classification.":[35,118],"Current":[36],"advanced":[37],"methods":[38,67],"use":[39],"private-shared":[41,144],"paradigm,":[42],"capturing":[43],"domain-shared":[44],"features":[45,91],"by":[46,100],"a":[47,52,82,143],"shared":[48],"encoder,":[49],"and":[50],"training":[51],"private":[53],"encoder":[54],"for":[55],"each":[56],"domain":[57],"extract":[59],"domain-specific":[60],"features.":[61],"However,":[62],"realistic":[64],"scenarios,":[65],"these":[66],"suffer":[68],"from":[69],"inefficiency":[70],"as":[71],"new":[72],"are":[74],"constantly":[75],"emerging.":[76],"In":[77],"this":[78,105],"paper,":[79],"we":[80,107],"propose":[81],"robust":[83],"contrastive":[84,102],"alignment":[85],"method":[86,125],"align":[88],"feature":[98,112],"space":[99],"supervised":[101],"learning.":[103],"By":[104],"means,":[106],"only":[108],"need":[109],"two":[110],"universal":[111],"extractors":[113],"achieve":[115],"Extensive":[119],"experimental":[120],"results":[121],"show":[122],"that":[123],"our":[124],"performs":[126],"on":[127],"par":[128],"or":[130],"sometimes":[131],"better":[132],"than":[133],"state-of-the-art":[135],"method,":[136],"uses":[138],"complex":[140],"multi-classifier":[141],"framework.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":5}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}