{"id":"https://openalex.org/W2566475380","doi":"https://doi.org/10.3233/fi-2016-1427","title":"Rough Hypercuboid Based Supervised Regularized Canonical Correlation for Multimodal Data Analysis*","display_name":"Rough Hypercuboid Based Supervised Regularized Canonical Correlation for Multimodal Data Analysis*","publication_year":2016,"publication_date":"2016-12-24","ids":{"openalex":"https://openalex.org/W2566475380","doi":"https://doi.org/10.3233/fi-2016-1427","mag":"2566475380"},"language":"en","primary_location":{"id":"doi:10.3233/fi-2016-1427","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2016-1427","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","raw_type":"journal-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/A5001103573","display_name":"Pradipta Maji","orcid":"https://orcid.org/0000-0002-8288-8917"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pradipta Maji","raw_affiliation_strings":["Biomedical Imaging and Bioinformatics Lab, Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700 108, West Bengal, India. E-mail: {pmaji,amandal}@isical.ac.in"],"affiliations":[{"raw_affiliation_string":"Biomedical Imaging and Bioinformatics Lab, Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700 108, West Bengal, India. E-mail: {pmaji,amandal}@isical.ac.in","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084469496","display_name":"Ankita Mandal","orcid":"https://orcid.org/0000-0002-2785-7915"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ankita Mandal","raw_affiliation_strings":["Biomedical Imaging and Bioinformatics Lab, Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700 108, West Bengal, India. E-mail: {pmaji,amandal}@isical.ac.in"],"affiliations":[{"raw_affiliation_string":"Biomedical Imaging and Bioinformatics Lab, Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700 108, West Bengal, India. E-mail: {pmaji,amandal}@isical.ac.in","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001103573"],"corresponding_institution_ids":["https://openalex.org/I6498739"],"apc_list":null,"apc_paid":null,"fwci":1.3939,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.84391746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"148","issue":"1-2","first_page":"133","last_page":"155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.8031761646270752},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.7477874159812927},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5586592555046082},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5585280656814575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5399792790412903},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44842132925987244},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4225430488586426},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.415882408618927},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4149585962295532},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4050545394420624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4012056887149811},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38565436005592346}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.8031761646270752},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.7477874159812927},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5586592555046082},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5585280656814575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5399792790412903},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44842132925987244},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4225430488586426},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.415882408618927},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4149585962295532},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4050545394420624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4012056887149811},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38565436005592346},{"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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/fi-2016-1427","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2016-1427","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1491070134","https://openalex.org/W1529350020","https://openalex.org/W1530625260","https://openalex.org/W1536675765","https://openalex.org/W1600470352","https://openalex.org/W1601833000","https://openalex.org/W1837217435","https://openalex.org/W1880944740","https://openalex.org/W1907621547","https://openalex.org/W1956744192","https://openalex.org/W1964529181","https://openalex.org/W1972745197","https://openalex.org/W1976670813","https://openalex.org/W1979850518","https://openalex.org/W1984837326","https://openalex.org/W1987858092","https://openalex.org/W1990745503","https://openalex.org/W2000692929","https://openalex.org/W2017634446","https://openalex.org/W2025341678","https://openalex.org/W2027654459","https://openalex.org/W2032017353","https://openalex.org/W2035713536","https://openalex.org/W2039332006","https://openalex.org/W2047028564","https://openalex.org/W2083303115","https://openalex.org/W2083700614","https://openalex.org/W2084237514","https://openalex.org/W2092044939","https://openalex.org/W2096393821","https://openalex.org/W2096663965","https://openalex.org/W2098093602","https://openalex.org/W2121703987","https://openalex.org/W2126400212","https://openalex.org/W2127314075","https://openalex.org/W2128771953","https://openalex.org/W2137205163","https://openalex.org/W2137396323","https://openalex.org/W2151064980","https://openalex.org/W2151101158","https://openalex.org/W2152707764","https://openalex.org/W2155423555","https://openalex.org/W2155834859","https://openalex.org/W2156909104","https://openalex.org/W2157582398","https://openalex.org/W2158012006","https://openalex.org/W2160050542","https://openalex.org/W2160307100","https://openalex.org/W2165015714","https://openalex.org/W2167283581","https://openalex.org/W2168523997","https://openalex.org/W2170341854","https://openalex.org/W2221309631","https://openalex.org/W2406319982","https://openalex.org/W2527621380"],"related_works":["https://openalex.org/W2392963705","https://openalex.org/W2107349454","https://openalex.org/W1565185441","https://openalex.org/W2382278777","https://openalex.org/W1964260090","https://openalex.org/W2353240132","https://openalex.org/W2375932290","https://openalex.org/W1486178390","https://openalex.org/W138553499","https://openalex.org/W2189693141"],"abstract_inverted_index":{"One":[0],"of":[1,58,61,84,110,117,120,122,142,144,155,168],"the":[2,48,56,82,111,115,130,140,153,169],"main":[3],"problems":[4],"in":[5,37,96,150,158],"real":[6,184],"life":[7,185],"omics":[8,101],"data":[9,23,45,102,164,186],"analysis":[10,31],"is":[11,180],"how":[12],"to":[13,90,138],"extract":[14,91],"relevant":[15,92],"and":[16,86,93],"non-redundant":[17,94,160],"features":[18,40,95,161],"from":[19,41,99,162],"high":[20],"dimensional":[21],"multimodal":[22,42,100,163],"sets.":[24,46,103,165,187],"In":[25,70],"general,":[26],"supervised":[27],"regularized":[28],"canonical":[29,62,123],"correlation":[30],"(SRCCA)":[32],"plays":[33],"an":[34,135],"important":[35],"role":[36],"extracting":[38,159],"new":[39,77],"om":[43],"ics":[44],"However,":[47],"existing":[49,178],"SRCCA":[50,78,85,112,156],"optimizes":[51,107],"regularization":[52,108],"parameters":[53,109],"based":[54,113],"on":[55,114,147,182],"quality":[57,116],"first":[59],"pair":[60],"variables":[63,124],"only":[64],"using":[65,125],"standard":[66],"feature":[67,148],"evaluation":[68],"indices.":[69],"this":[71,73],"regard,":[72],"paper":[74],"introduces":[75],"a":[76,118,174],"algorithm,":[79],"integrating":[80],"judiciously":[81],"merits":[83],"rough":[87,126,131],"hypercuboid":[88,127,132],"approach,":[89,171],"approximation":[97,151],"spaces":[98],"The":[104,166],"proposed":[105,170],"method":[106],"set":[119,149],"pairs":[121],"approach.":[128],"While":[129],"approach":[133],"provides":[134],"efficient":[136],"way":[137],"calculate":[139],"degree":[141],"dependency":[143],"class":[145],"labels":[146],"spaces,":[152],"merit":[154],"helps":[157],"effectiveness":[167],"along":[172],"with":[173,176],"comparison":[175],"related":[177],"approaches,":[179],"demonstrated":[181],"several":[183]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
