{"id":"https://openalex.org/W2403160752","doi":null,"title":"Linking heterogeneous input features with pivots for domain adaptation","display_name":"Linking heterogeneous input features with pivots for domain adaptation","publication_year":2015,"publication_date":"2015-07-25","ids":{"openalex":"https://openalex.org/W2403160752","mag":"2403160752"},"language":"en","primary_location":{"id":"mag:2403160752","doi":null,"is_oa":false,"landing_page_url":"https://www.ijcai.org/Proceedings/15/Papers/204.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419142","display_name":"International Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Artificial Intelligence","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5007102035","display_name":"Guangyou Zhou","orcid":"https://orcid.org/0000-0002-7675-6619","observed_orcids":["https://orcid.org/0000-0002-7675-6619"]},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyou Zhou","raw_affiliation_strings":["School of Computer, Central China, Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-7675-6619","affiliations":[{"raw_affiliation_string":"School of Computer, Central China, Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039602194","display_name":"Tingting He","orcid":"https://orcid.org/0000-0002-5677-2718","observed_orcids":["https://orcid.org/0000-0002-5677-2718"]},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingting He","raw_affiliation_strings":["School of Computer, Central China, Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-5677-2718","affiliations":[{"raw_affiliation_string":"School of Computer, Central China, Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061069727","display_name":"Wensheng Wu","orcid":"https://orcid.org/0000-0002-2948-9773","observed_orcids":["https://orcid.org/0000-0002-2948-9773"]},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wensheng Wu","raw_affiliation_strings":["Computer Science Department,University of Southern California, Los Angeles, CA"],"raw_orcid":"https://orcid.org/0000-0002-2948-9773","affiliations":[{"raw_affiliation_string":"Computer Science Department,University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101569679","display_name":"Xiaohua Tony Hu","orcid":"https://orcid.org/0000-0002-4777-3022","observed_orcids":["https://orcid.org/0000-0002-4777-3022","https://orcid.org/0009-0009-9813-8457"]},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Hu","raw_affiliation_strings":["School of Computer, Central China, Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-4777-3022","affiliations":[{"raw_affiliation_string":"School of Computer, Central China, Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3272,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.91472355,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1419","last_page":"1425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9771000146865845,"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":0.9771000146865845,"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":0.021800000220537186,"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":0.00039999998989515007,"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/domain-adaptation","display_name":"domain adaptation","score":0.9179999828338623},{"id":"https://openalex.org/keywords/sentiment-classification","display_name":"sentiment classification","score":0.9909999966621399},{"id":"https://openalex.org/keywords/pivot","display_name":"pivot","score":0.843999981880188},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"non-negative matrix factorization","score":0.8870000243186951},{"id":"https://openalex.org/keywords/topic-modeling","display_name":"topic modeling","score":0.6190000176429749},{"id":"https://openalex.org/keywords/user-generated-reviews","display_name":"user-generated reviews","score":0.722000002861023},{"id":"https://openalex.org/keywords/amazon-product-reviews","display_name":"Amazon reviews","score":0.6639999747276306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8424667119979858},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7124340534210205},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6988193988800049},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6984552145004272},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6666616797447205},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5711682438850403},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5696941614151001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5465507507324219},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4641709327697754},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.463521808385849},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.379395455121994},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33372244238853455},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07252421975135803},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.07018518447875977},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2403160752","doi":null,"is_oa":false,"landing_page_url":"https://www.ijcai.org/Proceedings/15/Papers/204.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419142","display_name":"International Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W159038999","https://openalex.org/W1914599625","https://openalex.org/W1932968309","https://openalex.org/W1967807490","https://openalex.org/W2015583498","https://openalex.org/W2068599126","https://openalex.org/W2076566842","https://openalex.org/W2092560274","https://openalex.org/W2096873754","https://openalex.org/W2097726431","https://openalex.org/W2108646579","https://openalex.org/W2110096996","https://openalex.org/W2123160630","https://openalex.org/W2130903752","https://openalex.org/W2131953535","https://openalex.org/W2135029798","https://openalex.org/W2151752537","https://openalex.org/W2153353890","https://openalex.org/W2158108973","https://openalex.org/W2166706824","https://openalex.org/W2215421138","https://openalex.org/W2250879510","https://openalex.org/W2251251137","https://openalex.org/W2251371340","https://openalex.org/W2397710600"],"related_works":["https://openalex.org/W2751820697","https://openalex.org/W2098803046","https://openalex.org/W2250370932","https://openalex.org/W2578983297","https://openalex.org/W2515059321","https://openalex.org/W2514769532","https://openalex.org/W22861983","https://openalex.org/W2741989495","https://openalex.org/W4285688121","https://openalex.org/W2145868540"],"abstract_inverted_index":{"Sentiment":[0],"classification":[1,58,161],"aims":[2],"to":[3,38,72,87],"automatically":[4],"predict":[5],"sentiment":[6,15,26,57,160],"polarity":[7],"(e.g.,":[8,17],"positive":[9],"or":[10],"negative)":[11],"of":[12,45,53,75,116,128,130,133],"user":[13,24],"generated":[14,25],"data":[16,27,42],"reviews,":[18],"blogs).":[19],"In":[20,82],"real":[21],"applications,":[22],"these":[23],"can":[28],"span":[29],"so":[30],"many":[31],"different":[32,79,108],"domains":[33,109],"that":[34,139],"it":[35],"is":[36,70,100,153],"difficult":[37],"manually":[39],"label":[40],"training":[41],"for":[43,56,159],"all":[44,119],"them.":[46],"Hence,":[47],"this":[48,83],"paper":[49],"studies":[50],"the":[51,104,114,145,156],"problem":[52],"domain":[54,69],"adaptation":[55],"where":[59],"a":[60,67,78,125],"system":[61],"trained":[62],"using":[63],"labeled":[64],"reviews":[65,76,129],"from":[66,107],"source":[68],"deployed":[71],"classify":[73],"sentiments":[74],"in":[77],"target":[80],"domain.":[81],"paper,":[84],"we":[85],"propose":[86],"link":[88],"heterogeneous":[89],"input":[90],"features":[91],"with":[92,113,155],"pivots":[93,117],"via":[94],"joint":[95],"non-negative":[96],"matrix":[97],"factorization.":[98],"This":[99],"achieved":[101],"by":[102],"learning":[103],"domain-specific":[105],"information":[106],"into":[110],"unified":[111],"topics,":[112],"help":[115],"across":[118],"domains.":[120],"We":[121],"conduct":[122],"experiments":[123],"on":[124],"benchmark":[126],"composed":[127],"4":[131],"types":[132],"Amazon":[134],"products.":[135],"Experimental":[136],"results":[137],"show":[138],"our":[140],"proposed":[141],"approach":[142],"significantly":[143],"outperforms":[144],"baseline":[146],"method,":[147],"and":[148],"achieves":[149],"an":[150],"accuracy":[151],"which":[152],"competitive":[154],"state-of-the-art":[157],"methods":[158],"adaptation.":[162]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
