{"id":"https://openalex.org/W3168216295","doi":"https://doi.org/10.1109/cscwd49262.2021.9437718","title":"A Collaboration Multi-Domain Sentiment Classification on Specific Domain and Global Features","display_name":"A Collaboration Multi-Domain Sentiment Classification on Specific Domain and Global Features","publication_year":2021,"publication_date":"2021-05-05","ids":{"openalex":"https://openalex.org/W3168216295","doi":"https://doi.org/10.1109/cscwd49262.2021.9437718","mag":"3168216295"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd49262.2021.9437718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd49262.2021.9437718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","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/A5000121518","display_name":"Junping He","orcid":"https://orcid.org/0009-0009-6165-3009"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junping He","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003969171","display_name":"Shaohua Teng","orcid":"https://orcid.org/0000-0002-7204-1288"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Teng","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101726684","display_name":"Lunke Fei","orcid":"https://orcid.org/0000-0001-6072-7875"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lunke Fei","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052008856","display_name":"Xiaozhao Fang","orcid":"https://orcid.org/0000-0001-8440-1765"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaozhao Fang","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100349334","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0003-2747-1622"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000121518"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06942091,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"323","last_page":"328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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/T11550","display_name":"Text and Document Classification Technologies","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/T10028","display_name":"Topic Modeling","score":0.9955000281333923,"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":0.7985260486602783},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7858690023422241},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7333483695983887},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6392723321914673},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6071873903274536},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5340100526809692},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4195812940597534},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4193309545516968},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3734930455684662},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3317040205001831},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09242722392082214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7985260486602783},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7858690023422241},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7333483695983887},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6392723321914673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6071873903274536},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5340100526809692},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4195812940597534},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4193309545516968},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3734930455684662},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3317040205001831},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09242722392082214},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd49262.2021.9437718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd49262.2021.9437718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G4198728212","display_name":null,"funder_award_id":"17ZK0422","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G4616656708","display_name":null,"funder_award_id":"61702110,61772141,61972102,62006048","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1467160992","https://openalex.org/W1614298861","https://openalex.org/W1970696760","https://openalex.org/W1985048767","https://openalex.org/W2058339786","https://openalex.org/W2065069176","https://openalex.org/W2096794053","https://openalex.org/W2113609017","https://openalex.org/W2141819498","https://openalex.org/W2143455647","https://openalex.org/W2163302275","https://openalex.org/W2166706824","https://openalex.org/W2311769156","https://openalex.org/W2532602960","https://openalex.org/W2586733088","https://openalex.org/W2588703347","https://openalex.org/W2687524069","https://openalex.org/W2798199013","https://openalex.org/W2800344590","https://openalex.org/W2801011252","https://openalex.org/W2805548989","https://openalex.org/W2906441821","https://openalex.org/W2914733877","https://openalex.org/W2950577311","https://openalex.org/W2959988970","https://openalex.org/W2963739429"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4292388283","https://openalex.org/W3204418343","https://openalex.org/W4287241967","https://openalex.org/W3144173820","https://openalex.org/W1560624709","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3111760155"],"abstract_inverted_index":{"Sentiment":[0],"classification":[1,28,101,161,186],"has":[2,29],"been":[3,30],"attracting":[4],"increasing":[5],"attention":[6],"with":[7,49,103],"the":[8,15,39,47,74,84,87,117,123,144,147,151,154,175,181],"growth":[9],"of":[10,24,53,146,153,183],"textual":[11],"data":[12,19,81],"created":[13],"on":[14,170],"Internet.":[16],"Text":[17],"review":[18],"covers":[20],"a":[21,34,50,94,108,157],"wide":[22],"range":[23],"field,":[25],"and":[26,97,121,134,187],"sentiment":[27,100,110,125,128,132,136,140,160,185],"widely":[31],"known":[32],"as":[33,150],"highly":[35],"domain-dependent":[36],"problem.":[37],"Unfortunately,":[38],"existing":[40],"methods":[41],"have":[42,78],"achieved":[43],"good":[44],"results":[45,169],"in":[46],"domain":[48,64,67,76,119],"large":[51],"number":[52],"labeled":[54],"training":[55],"data.":[56],"Some":[57],"researchers":[58],"apply":[59],"classifiers":[60],"learned":[61],"from":[62],"source":[63,114,118],"to":[65,77,82],"target":[66,75],"through":[68],"transfer":[69],"learning,":[70],"which":[71],"still":[72],"requires":[73],"enough":[79],"unlabeled":[80],"learn":[83],"similarity":[85],"between":[86],"domains.":[88],"In":[89],"this":[90],"paper,":[91],"we":[92],"propose":[93],"collaborative":[95],"domain-specific":[96,109,131],"global":[98,124,135],"multi-domain":[99,184],"approaches":[102],"logistic":[104,166],"regression.":[105,167],"We":[106],"train":[107,122],"classifier":[111,129,137],"for":[112],"each":[113],"domain,":[115],"reconstruct":[116],"datasets,":[120],"classifiers.":[126],"Domain-specific":[127],"captures":[130,138],"features,":[133],"general":[139],"knowledge.":[141],"Finally,":[142],"taking":[143],"output":[145],"first":[148],"layer":[149],"input":[152],"second":[155],"layer,":[156],"two-level":[158],"cross-domain":[159],"model":[162],"is":[163],"constructed":[164],"by":[165],"Experimental":[168],"benchmark":[171],"datasets":[172],"show":[173],"that":[174],"proposed":[176],"approach":[177],"can":[178],"effectively":[179],"improve":[180],"performance":[182],"significantly":[188],"outperform":[189],"baseline":[190],"methods.":[191]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}