{"id":"https://openalex.org/W4233436991","doi":"https://doi.org/10.1109/icpr.2004.1333853","title":"Order-preserving clustering and its application to gene expression data","display_name":"Order-preserving clustering and its application to gene expression data","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W4233436991","doi":"https://doi.org/10.1109/icpr.2004.1333853"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2004.1333853","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1333853","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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/A5083063028","display_name":"T. Syeda-Mahmood","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"T. Syeda-Mahmood","raw_affiliation_strings":["IBM Almaden Research Center, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"IBM Almaden Research Center, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210085935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5083063028"],"corresponding_institution_ids":["https://openalex.org/I4210085935"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39635535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"637","last_page":"640 Vol.4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9524000287055969,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9466999769210815,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8725535869598389},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7492966651916504},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5798474550247192},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5535668134689331},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5287622809410095},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5080504417419434},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5052030682563782},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49464961886405945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4875907301902771},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4715844690799713},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.45234620571136475},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.4514634907245636},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.4268716871738434},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.42251789569854736},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.400871217250824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3833887577056885},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13006848096847534}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8725535869598389},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7492966651916504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5798474550247192},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5535668134689331},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5287622809410095},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5080504417419434},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5052030682563782},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49464961886405945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4875907301902771},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4715844690799713},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.45234620571136475},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.4514634907245636},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.4268716871738434},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.42251789569854736},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.400871217250824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3833887577056885},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13006848096847534},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2004.1333853","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1333853","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1536815449","https://openalex.org/W2029485495","https://openalex.org/W2034501924","https://openalex.org/W2057632640","https://openalex.org/W2103453943","https://openalex.org/W2133155955","https://openalex.org/W2142460132","https://openalex.org/W2160091849","https://openalex.org/W6632204590","https://openalex.org/W6664271236","https://openalex.org/W6679681355"],"related_works":["https://openalex.org/W2111119584","https://openalex.org/W3186815950","https://openalex.org/W2389934482","https://openalex.org/W2590117803","https://openalex.org/W2111827030","https://openalex.org/W2040929534","https://openalex.org/W3168768270","https://openalex.org/W2388628913","https://openalex.org/W2202413591","https://openalex.org/W2393707058"],"abstract_inverted_index":{"Clustering":[0,63],"of":[1,52,64,81],"ordered":[2,58,141],"data":[3,23,53,66,144],"sets":[4,145],"is":[5,93,126],"a":[6,43,61,78],"common":[7],"problem":[8],"faced":[9],"in":[10,110],"many":[11],"pattern":[12],"recognition":[13],"tasks.":[14],"Existing":[15],"clustering":[16,46,125],"methods":[17],"either":[18],"fail":[19],"to":[20,34,69,117,123],"capture":[21],"the":[22,36,65,97,105,140],"or":[24,31,91],"use":[25],"restrictive":[26],"models":[27,33],"such":[28,111],"as":[29,60],"HMMs":[30],"AR":[32],"model":[35],"data.":[37],"In":[38],"this":[39],"paper,":[40],"we":[41],"present":[42],"general":[44],"order-preserving":[45],"algorithm":[47,121],"that":[48,113,129],"allows":[49],"arbitrary":[50],"patterns":[51],"evolution":[54],"by":[55,95],"representing":[56],"each":[57],"set":[59],"curve.":[62],"then":[67,127],"reduces":[68],"grouping":[70],"curves":[71,85,99,102,112,132],"based":[72],"on":[73,139],"shape":[74,82,118],"similarity.":[75],"We":[76],"develop":[77],"novel":[79],"measure":[80],"similarity":[83,90],"between":[84],"using":[86],"scale-space":[87],"distance.":[88],"Shape":[89],"dis-similarity":[92],"judged":[94],"composing":[96],"higher-dimensional":[98],"from":[100,147],"constituent":[101],"and":[103,108],"noting":[104],"additional":[106],"twists":[107],"turns":[109],"can":[114],"be":[115],"attributed":[116],"differences.":[119],"An":[120],"analogous":[122],"K-means":[124],"developed":[128],"uses":[130],"prototypical":[131],"for":[133],"cluster":[134],"representation.":[135],"Results":[136],"are":[137],"demonstrated":[138],"gene":[142,148],"expression":[143],"obtained":[146],"chips.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}