{"id":"https://openalex.org/W2942635345","doi":"https://doi.org/10.1109/iscas.2019.8702470","title":"A Novel Weighted Hybrid Multi-View Fusion Algorithm for Semi-Supervised Classification","display_name":"A Novel Weighted Hybrid Multi-View Fusion Algorithm for Semi-Supervised Classification","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2942635345","doi":"https://doi.org/10.1109/iscas.2019.8702470","mag":"2942635345"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2019.8702470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5082259804","display_name":"Song Wang","orcid":"https://orcid.org/0000-0003-4152-5295"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Wang","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101507341","display_name":"Xin Guo","orcid":"https://orcid.org/0000-0003-4153-4642"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Guo","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101112071","display_name":"Yun Tie","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Tie","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326349","display_name":"Lin Qi","orcid":"https://orcid.org/0000-0002-4558-6741"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Qi","raw_affiliation_strings":["School of Information Engineering, Zhengzhou University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001287866","display_name":"Ling Guan","orcid":"https://orcid.org/0000-0002-2681-2504"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ling Guan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1017,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41590691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"9","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965999722480774,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965999722480774,"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/T10057","display_name":"Face and Expression Recognition","score":0.996399998664856,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6897708773612976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6835168600082397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5865843296051025},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5668221116065979},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5655787587165833},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5286581516265869},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5014233589172363},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4854331612586975},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47646021842956543},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4756614565849304},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.43416279554367065},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.42096149921417236},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40031978487968445},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38381630182266235},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36203038692474365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17873528599739075},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16581329703330994}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6897708773612976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6835168600082397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5865843296051025},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5668221116065979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5655787587165833},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5286581516265869},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5014233589172363},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4854331612586975},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47646021842956543},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4756614565849304},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.43416279554367065},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.42096149921417236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40031978487968445},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38381630182266235},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36203038692474365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17873528599739075},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16581329703330994},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscas.2019.8702470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2019.8702470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},{"id":"mag:3035052492","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902279497257555","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W213042921","https://openalex.org/W1944448017","https://openalex.org/W1969698720","https://openalex.org/W1981613567","https://openalex.org/W1990334093","https://openalex.org/W1991825408","https://openalex.org/W1992652404","https://openalex.org/W1999693420","https://openalex.org/W2017475521","https://openalex.org/W2019288156","https://openalex.org/W2024051019","https://openalex.org/W2025341678","https://openalex.org/W2031823405","https://openalex.org/W2048871128","https://openalex.org/W2053101950","https://openalex.org/W2058001207","https://openalex.org/W2083138589","https://openalex.org/W2103972604","https://openalex.org/W2125290066","https://openalex.org/W2129927619","https://openalex.org/W2139395976","https://openalex.org/W2153959628","https://openalex.org/W2156503193","https://openalex.org/W2163532725","https://openalex.org/W2164507085","https://openalex.org/W2315630905","https://openalex.org/W2573473305","https://openalex.org/W2579597427","https://openalex.org/W2619383789","https://openalex.org/W2741807795","https://openalex.org/W2765179532","https://openalex.org/W2794595914","https://openalex.org/W2794827501","https://openalex.org/W2804104424","https://openalex.org/W3134705486","https://openalex.org/W4210997624","https://openalex.org/W4250589301","https://openalex.org/W6608583218","https://openalex.org/W6640526699","https://openalex.org/W6678885645","https://openalex.org/W6679453042","https://openalex.org/W6731811539","https://openalex.org/W6732222342"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2152662039","https://openalex.org/W1586607209","https://openalex.org/W122912556","https://openalex.org/W4312414840","https://openalex.org/W2621411691","https://openalex.org/W2271357838"],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1,6],"aims":[2],"to":[3,58,79],"improve":[4],"the":[5,19,37,47,51,60,70,84,94,97],"performance":[7],"with":[8,72],"very":[9],"limited":[10],"label":[11],"information.":[12],"To":[13],"dig":[14],"more":[15,73],"available":[16],"information":[17],"from":[18],"collected":[20],"data,":[21],"we":[22],"propose":[23],"a":[24],"weighted":[25],"hybrid":[26],"multi-view":[27],"feature":[28],"fusion":[29,53,85],"approach":[30],"for":[31,41,55],"semi-supervised":[32],"classification":[33],"problem.":[34],"Specifically,":[35],"under":[36],"rank":[38],"consistency":[39],"constraint":[40],"labels":[42],"predicted":[43],"by":[44],"view-specific":[45],"learners,":[46],"proposed":[48,98],"method":[49],"estimates":[50],"optimal":[52],"weight":[54],"each":[56],"learner":[57],"balance":[59],"incomparable":[61],"square":[62],"losses":[63],"on":[64,89],"different":[65],"views.":[66],"In":[67],"this":[68],"case,":[69],"learners":[71],"powerful":[74],"prediction":[75],"capability":[76],"are":[77],"pushed":[78],"have":[80],"higher":[81],"weights":[82],"during":[83],"process.":[86],"Experimental":[87],"results":[88],"6":[90],"real-world":[91],"datasets":[92],"demonstrate":[93],"effectiveness":[95],"of":[96],"technique.":[99]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
