{"id":"https://openalex.org/W2141384447","doi":"https://doi.org/10.1109/ccis.2014.7175703","title":"Cross-domain sentiment classification using deep learning approach","display_name":"Cross-domain sentiment classification using deep learning approach","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W2141384447","doi":"https://doi.org/10.1109/ccis.2014.7175703","mag":"2141384447"},"language":"en","primary_location":{"id":"doi:10.1109/ccis.2014.7175703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis.2014.7175703","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems","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/A5113176094","display_name":"Miao Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Miao Sun","raw_affiliation_strings":["South China Normal University, Guangzhou, China","South China Nomal University, Guangzhou 510631, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Nomal University, Guangzhou 510631, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102746545","display_name":"Qi Tan","orcid":"https://orcid.org/0000-0002-0831-7999"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tan","raw_affiliation_strings":["South China Normal University, Guangzhou, China","South China Nomal University, Guangzhou 510631, China"],"affiliations":[{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Nomal University, Guangzhou 510631, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038044561","display_name":"Runwei Ding","orcid":"https://orcid.org/0000-0003-4987-0405"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runwei Ding","raw_affiliation_strings":["Peking University, Shenzhen Graduate School, Shenzhen, China","Peking University Shenzhen Graduate School, 518055, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210128628"]},{"raw_affiliation_string":"Peking University Shenzhen Graduate School, 518055, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100410352","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0003-1640-9620"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Peking University, Beijing, China","Peking University,Beijing 100087,China)"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University,Beijing 100087,China)","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113176094"],"corresponding_institution_ids":["https://openalex.org/I187400657"],"apc_list":null,"apc_paid":null,"fwci":0.2439,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.61753741,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"60","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10320","display_name":"Neural Networks and Applications","score":0.996999979019165,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958000183105469,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7935853004455566},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7254651784896851},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6315572261810303},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5650320053100586},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5372742414474487},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49698856472969055},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4537409543991089},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42951536178588867},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1469039022922516}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7935853004455566},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7254651784896851},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6315572261810303},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5650320053100586},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5372742414474487},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49698856472969055},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4537409543991089},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42951536178588867},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1469039022922516},{"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},{"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:10.1109/ccis.2014.7175703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis.2014.7175703","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W4952878","https://openalex.org/W22861983","https://openalex.org/W122553268","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W2096873754","https://openalex.org/W2100495367","https://openalex.org/W2105523772","https://openalex.org/W2107789863","https://openalex.org/W2112483442","https://openalex.org/W2120354757","https://openalex.org/W2140262144","https://openalex.org/W2145094598","https://openalex.org/W2153635508","https://openalex.org/W2158108973","https://openalex.org/W2949821452","https://openalex.org/W2997574889","https://openalex.org/W3120421331","https://openalex.org/W3146885639","https://openalex.org/W6600949241","https://openalex.org/W6604970484","https://openalex.org/W6675865240","https://openalex.org/W6676071220","https://openalex.org/W6676840641","https://openalex.org/W6681096077"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Deep":[0],"learning,":[1],"as":[2],"a":[3,41],"new":[4,20],"unsupervised":[5],"leaning":[6],"algorithm,":[7,54],"has":[8,17],"strong":[9],"capabilities":[10],"to":[11,28,73,90],"learn":[12,57],"data":[13,123],"representations.":[14],"Previous":[15],"work":[16],"shown":[18],"that":[19,104],"features":[21,61],"learned":[22],"by":[23],"deep":[24],"learning":[25],"algorithm":[26,72,106,114],"help":[27],"improve":[29,75],"the":[30,76,92,108,112,117,122],"accuracy":[31,77],"of":[32,44,78],"cross-domain":[33,79,93],"classification.":[34,80],"In":[35,65],"this":[36],"paper,":[37],"we":[38,67,82],"firstly":[39],"propose":[40],"modified":[42],"version":[43],"marginalized":[45],"stacked":[46],"denoising":[47],"autoencoders":[48],"(mSDA).":[49],"We":[50],"call":[51],"it":[52],"mSDA++":[53,113],"which":[55],"can":[56,115],"excellent":[58],"and":[59,87,120],"low-dimensional":[60],"for":[62],"training":[63],"classifier.":[64],"addition,":[66],"combine":[68],"mSDA":[69],"with":[70],"EASYADAPT":[71],"further":[74],"Then":[81],"use":[83],"SVM,":[84],"mSDA,":[85],"mSDA++,":[86],"EA+mSDA":[88,105],"algorithms":[89],"do":[91],"sentiment":[94],"classification":[95],"experiments":[96],"on":[97],"Amazon":[98],"benchmark":[99],"dataset.":[100],"The":[101],"results":[102],"show":[103],"attains":[107],"best":[109],"accuracy.":[110],"Besides,":[111],"accelerate":[116],"subsequent":[118],"calculation":[119],"reduce":[121],"storage":[124],"space.":[125]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}