{"id":"https://openalex.org/W2794381107","doi":"https://doi.org/10.3233/ida-163337","title":"Feature clustering dimensionality reduction based on affinity propagation","display_name":"Feature clustering dimensionality reduction based on affinity propagation","publication_year":2018,"publication_date":"2018-03-14","ids":{"openalex":"https://openalex.org/W2794381107","doi":"https://doi.org/10.3233/ida-163337","mag":"2794381107"},"language":"en","primary_location":{"id":"doi:10.3233/ida-163337","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-163337","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"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":"Intelligent Data Analysis","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/A5030903526","display_name":"Yahong Zhang","orcid":"https://orcid.org/0000-0003-1148-949X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yahong Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101457814","display_name":"Yujian Li","orcid":"https://orcid.org/0000-0002-4991-6461"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yujian Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100738839","display_name":"Ting Zhang","orcid":"https://orcid.org/0000-0002-1899-1784"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ting Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057624061","display_name":"Pius Kwao Gadosey","orcid":"https://orcid.org/0000-0003-0454-274X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pius Kwao Gadosey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5064487134","display_name":"Zhaoying Liu","orcid":"https://orcid.org/0000-0001-6991-0123"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaoying Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5101457814"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3121,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60089554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"22","issue":"2","first_page":"309","last_page":"323"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9958000183105469,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9894999861717224,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7858095169067383},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6509577631950378},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6411676406860352},{"id":"https://openalex.org/keywords/affinity-propagation","display_name":"Affinity propagation","score":0.6120268702507019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5785028338432312},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5434865951538086},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4697810709476471},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4677225351333618},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3948269784450531},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.1616990566253662},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.08896824717521667}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7858095169067383},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6509577631950378},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6411676406860352},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.6120268702507019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5785028338432312},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5434865951538086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4697810709476471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4677225351333618},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3948269784450531},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.1616990566253662},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.08896824717521667},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/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/ida-163337","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-163337","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"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":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2001141328","https://openalex.org/W2007461126","https://openalex.org/W2017787659","https://openalex.org/W2023205960","https://openalex.org/W2025210087","https://openalex.org/W2036887984","https://openalex.org/W2043772506","https://openalex.org/W2053186076","https://openalex.org/W2064580901","https://openalex.org/W2103250033","https://openalex.org/W2105499314","https://openalex.org/W2115694019","https://openalex.org/W2119869458","https://openalex.org/W2127314673","https://openalex.org/W2135904200","https://openalex.org/W2137570937","https://openalex.org/W2138570191","https://openalex.org/W2140833774","https://openalex.org/W2145979309","https://openalex.org/W2156504490","https://openalex.org/W2156718197","https://openalex.org/W2158194116","https://openalex.org/W2165232124","https://openalex.org/W2165700458","https://openalex.org/W2168489973","https://openalex.org/W2168809519","https://openalex.org/W2625777111","https://openalex.org/W3106063097","https://openalex.org/W4285719527","https://openalex.org/W6676932568","https://openalex.org/W6680765659","https://openalex.org/W6682686508","https://openalex.org/W7034449035"],"related_works":["https://openalex.org/W2152028285","https://openalex.org/W2339674921","https://openalex.org/W3089862173","https://openalex.org/W2015538044","https://openalex.org/W2883447302","https://openalex.org/W2889059817","https://openalex.org/W2090269531","https://openalex.org/W2052253960","https://openalex.org/W2066259560","https://openalex.org/W2095834362"],"abstract_inverted_index":{"Feature":[0],"clustering":[1,40],"is":[2,112],"a":[3,37,50,59],"powerful":[4],"technique":[5],"for":[6,46,79],"dimensionality":[7,47,82,140],"reduction.":[8,48],"However,":[9],"existing":[10],"approaches":[11],"require":[12],"the":[13,54,81,84,92,104,124],"number":[14,93],"of":[15,61,83,91,94,108,128,149],"clusters":[16,62,95],"to":[17,122,134],"be":[18,70],"given":[19,51],"in":[20,75,115,147],"advance":[21],"or":[22],"controlled":[23],"by":[24,29,63],"parameters.":[25],"In":[26,120],"this":[27],"paper,":[28],"combining":[30],"with":[31,137],"affinity":[32],"propagation":[33],"(AP),":[34],"we":[35],"propose":[36],"new":[38,66],"feature":[39,67,117],"(FC)":[41],"algorithm,":[42],"ca":[43],"lled":[44],"APFC,":[45,129],"For":[49],"training":[52],"dataset,":[53],"original":[55,85],"features":[56],"automatically":[57],"form":[58],"bunch":[60],"AP.":[64],"A":[65],"can":[68],"then":[69],"extracted":[71,97],"from":[72],"each":[73],"cluster":[74],"three":[76,138],"different":[77],"ways":[78],"reducing":[80],"data.":[86],"APFC":[87],"requires":[88],"no":[89],"provision":[90],"(or":[96],"features)":[98],"beforehand.":[99],"Moreover,":[100],"it":[101,136],"avoids":[102],"computing":[103],"eigenvalues":[105],"and":[106,126,152],"eigenvectors":[107],"covariance":[109],"matrix":[110],"which":[111],"often":[113],"necessary":[114],"many":[116],"extraction":[118],"methods.":[119],"order":[121],"demonstrate":[123],"effectiveness":[125],"efficiency":[127],"extensive":[130],"experiments":[131],"are":[132],"conducted":[133],"compare":[135],"well-established":[139],"reduction":[141],"methods":[142],"on":[143],"14":[144],"UCI":[145],"datasets":[146],"terms":[148],"classification":[150],"accuracy":[151],"computational":[153],"time.":[154]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-23T06:36:01.041984","created_date":"2025-10-10T00:00:00"}
