{"id":"https://openalex.org/W2792807660","doi":"https://doi.org/10.1007/s10618-018-0558-x","title":"SICA: subjectively interesting component analysis","display_name":"SICA: subjectively interesting component analysis","publication_year":2018,"publication_date":"2018-03-08","ids":{"openalex":"https://openalex.org/W2792807660","doi":"https://doi.org/10.1007/s10618-018-0558-x","mag":"2792807660"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-018-0558-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-018-0558-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-018-0558-x.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-018-0558-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090926391","display_name":"Bo Kang","orcid":"https://orcid.org/0000-0002-9895-9927"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Bo Kang","raw_affiliation_strings":["Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium"],"raw_orcid":"https://orcid.org/0000-0002-9895-9927","affiliations":[{"raw_affiliation_string":"Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032448836","display_name":"Jefrey Lijffijt","orcid":"https://orcid.org/0000-0002-2930-5057"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jefrey Lijffijt","raw_affiliation_strings":["Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028764929","display_name":"Ra\u00fal Santos\u2010Rodr\u00edguez","orcid":"https://orcid.org/0000-0001-9576-3905"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ra\u00fal Santos-Rodr\u00edguez","raw_affiliation_strings":["Data Science Lab, University of Bristol, Bristol, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Lab, University of Bristol, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076045275","display_name":"Tijl De Bie","orcid":"https://orcid.org/0000-0002-2692-7504"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Tijl De Bie","raw_affiliation_strings":["Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Information Systems, IDLab, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090926391"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.6758,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.76707694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"32","issue":"4","first_page":"949","last_page":"987"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9962000250816345,"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/T10320","display_name":"Neural Networks and Applications","score":0.9962000250816345,"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/T10057","display_name":"Face and Expression Recognition","score":0.9908999800682068,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7405107617378235},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.7069060206413269},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6557725071907043},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6376340985298157},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5850962996482849},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5393627882003784},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5052927136421204},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.49662524461746216},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4741969704627991},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46616560220718384},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4608478248119354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4074001908302307},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3840159475803375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7405107617378235},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.7069060206413269},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6557725071907043},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6376340985298157},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5850962996482849},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5393627882003784},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5052927136421204},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.49662524461746216},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4741969704627991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46616560220718384},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4608478248119354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4074001908302307},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3840159475803375},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s10618-018-0558-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-018-0558-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-018-0558-x.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire/1812b279-c263-43d5-bd6c-2d57eb5d040e","is_oa":true,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/1812b279-c263-43d5-bd6c-2d57eb5d040e","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kang, B, Lijffijt, J, Santos-Rodr\u00edguez, R & de Bie, T 2018, 'SICA : subjectively interesting component analysis', Data Mining and Knowledge Discovery. https://doi.org/10.1007/s10618-018-0558-x","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:archive.ugent.be:8554235","is_oa":true,"landing_page_url":"https://biblio.ugent.be/publication/8554235","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1573-756X","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s10618-018-0558-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-018-0558-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-018-0558-x.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2602915566","display_name":null,"funder_award_id":"EP/M000060/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G2761285720","display_name":null,"funder_award_id":"FP/2007-2013","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2885645852","display_name":null,"funder_award_id":"No. 665501","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G2988008325","display_name":"Data Science for the Detection of Emerging Music Styles","funder_award_id":"EP/M000060/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3997584659","display_name":null,"funder_award_id":"665501","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G442989154","display_name":null,"funder_award_id":"FP/2007-2013","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G483950878","display_name":null,"funder_award_id":"G0F9816N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G5593277320","display_name":null,"funder_award_id":"2007-2013","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6621798171","display_name":null,"funder_award_id":"G091017N, G0F9816N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G7118244760","display_name":null,"funder_award_id":"665501","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G7595416141","display_name":null,"funder_award_id":"G091017N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G8057144507","display_name":"Formalizing Subjective Interestingness in Exploratory Data Mining","funder_award_id":"615517","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2792807660.pdf","grobid_xml":"https://content.openalex.org/works/W2792807660.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1163549746","https://openalex.org/W1548802052","https://openalex.org/W1579925870","https://openalex.org/W1988219946","https://openalex.org/W1990293817","https://openalex.org/W1994432310","https://openalex.org/W2001141328","https://openalex.org/W2001619934","https://openalex.org/W2012579006","https://openalex.org/W2025341678","https://openalex.org/W2046079134","https://openalex.org/W2076743544","https://openalex.org/W2082612735","https://openalex.org/W2097308346","https://openalex.org/W2101556484","https://openalex.org/W2104780023","https://openalex.org/W2106053110","https://openalex.org/W2113055885","https://openalex.org/W2121496884","https://openalex.org/W2123921160","https://openalex.org/W2125874614","https://openalex.org/W2129283471","https://openalex.org/W2132914434","https://openalex.org/W2141224535","https://openalex.org/W2143428259","https://openalex.org/W2154872931","https://openalex.org/W2164340936","https://openalex.org/W2167623372","https://openalex.org/W2187483593","https://openalex.org/W2294798173","https://openalex.org/W2366913357","https://openalex.org/W2613161123","https://openalex.org/W2747485148","https://openalex.org/W3099514962","https://openalex.org/W3141595720","https://openalex.org/W3148198191","https://openalex.org/W4237723258","https://openalex.org/W4246354968"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W2593948145","https://openalex.org/W2771038650","https://openalex.org/W2012491005","https://openalex.org/W2165670234","https://openalex.org/W1556684859","https://openalex.org/W4233188012","https://openalex.org/W1823429587","https://openalex.org/W2564294503","https://openalex.org/W2922457425"],"abstract_inverted_index":{"The":[0,34,67,143,236],"information":[1],"in":[2],"high-dimensional":[3],"datasets":[4],"is":[5,39,112,120,136,146,161],"often":[6],"too":[7],"complex":[8],"for":[9,63,80,115,140],"human":[10],"users":[11,242],"to":[12,20,25,77,93,138,156,203,243],"perceive":[13],"directly.":[14],"Hence,":[15],"it":[16,111],"may":[17,85,152],"be":[18,32,153],"helpful":[19],"use":[21],"dimensionality":[22,65],"reduction":[23],"methods":[24],"construct":[26,43],"lower":[27],"dimensional":[28,48],"representations":[29,95],"that":[30,37,70,96,210,239],"can":[31],"visualized.":[33],"natural":[35],"question":[36,53],"arises":[38],"how":[40],"do":[41],"we":[42,206,211],"a":[44,60,83,123,126,176,198,208,222],"most":[45],"informative":[46],"low":[47],"representation?":[49],"We":[50,100,168],"study":[51,169],"this":[52],"from":[54],"an":[55],"information-theoretic":[56],"perspective":[57],"and":[58,109,160],"introduce":[59],"new":[61],"method":[62,103],"linear":[64],"reduction.":[66],"obtained":[68,220],"model":[69,124],"quantifies":[71],"the":[72,88,102,131,149,157,165,180,183,187,201],"informativeness":[73],"also":[74],"allows":[75],"us":[76,92],"flexibly":[78],"account":[79],"prior":[81,173],"knowledge":[82,230],"user":[84,150,177,199,223],"have":[86,204],"about":[87,130,231],"data.":[89,132],"This":[90,133],"enables":[91,241],"provide":[94],"are":[97,219],"subjectively":[98,245],"interesting.":[99],"title":[101],"Subjectively":[104],"Interesting":[105],"Component":[106,193],"Analysis":[107,194],"(SICA)":[108],"expect":[110],"mainly":[113],"useful":[114],"iterative":[116],"data":[117,158,202,234],"mining.":[118],"SICA":[119,185,240],"based":[121],"on":[122],"of":[125,172,182],"user\u2019s":[127],"belief":[128,134],"state":[129,135,145],"used":[137],"search":[139],"surprising":[141],"views.":[142],"initial":[144],"chosen":[147],"by":[148],"(it":[151],"empty":[154],"up":[155],"format)":[159],"updated":[162],"automatically":[163],"as":[164,191,229],"analysis":[166],"progresses.":[167],"several":[170],"types":[171],"beliefs:":[174],"if":[175,197],"only":[178],"knows":[179],"scale":[181],"data,":[184],"yields":[186],"same":[188],"cost":[189],"function":[190],"Principal":[192],"(PCA),":[195],"while":[196],"expects":[200],"outliers,":[205],"obtain":[207],"variant":[209],"term":[212],"t-PCA.":[213],"Finally,":[214],"scientifically":[215],"more":[216,225,246],"interesting":[217,247],"variants":[218],"when":[221],"has":[224],"complicated":[226],"beliefs,":[227],"such":[228],"similarities":[232],"between":[233],"points.":[235],"experiments":[237],"suggest":[238],"find":[244],"representations.":[248]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2025-10-10T00:00:00"}
