{"id":"https://openalex.org/W2070404755","doi":"https://doi.org/10.1109/fskd.2014.6980856","title":"A common-subsequence-based approach for mining deep order preserving submatrix","display_name":"A common-subsequence-based approach for mining deep order preserving submatrix","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2070404755","doi":"https://doi.org/10.1109/fskd.2014.6980856","mag":"2070404755"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2014.6980856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2014.6980856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5015564248","display_name":"Yun Xue","orcid":"https://orcid.org/0000-0002-4048-5298"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Xue","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030624242","display_name":"Tiechen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiechen Li","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100628019","display_name":"Zhiwen Liu","orcid":"https://orcid.org/0000-0002-0743-4237"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Liu","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084976184","display_name":"Zhengling Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengling Liao","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101568340","display_name":"Hua Xiao","orcid":"https://orcid.org/0000-0003-3407-7009"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Xiao","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055100812","display_name":"Hongya Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongya Zhao","raw_affiliation_strings":["Shenzhen Polytechnic, Industrial Center, Shenzhen, China","Industrial Center, Shenzhen Polytechnic, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Polytechnic, Industrial Center, Shenzhen, China","institution_ids":["https://openalex.org/I182722699"]},{"raw_affiliation_string":"Industrial Center, Shenzhen Polytechnic, Shenzhen, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100740224","display_name":"Xiaohui Hu","orcid":"https://orcid.org/0000-0001-5717-8676"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Hu","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"292","issue":null,"first_page":"334","last_page":"340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10885","display_name":"Gene expression and cancer classification","score":0.9952999949455261,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9645000100135803,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6895618438720703},{"id":"https://openalex.org/keywords/longest-common-subsequence-problem","display_name":"Longest common subsequence problem","score":0.6813409328460693},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.6709334254264832},{"id":"https://openalex.org/keywords/subsequence","display_name":"Subsequence","score":0.6114639639854431},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5708708763122559},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48426908254623413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47663721442222595},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.46542972326278687},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4182016849517822},{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.41534852981567383},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3811473548412323},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.30516648292541504},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18268737196922302}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6895618438720703},{"id":"https://openalex.org/C120098539","wikidata":"https://www.wikidata.org/wiki/Q141001","display_name":"Longest common subsequence problem","level":2,"score":0.6813409328460693},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.6709334254264832},{"id":"https://openalex.org/C137877099","wikidata":"https://www.wikidata.org/wiki/Q1332977","display_name":"Subsequence","level":3,"score":0.6114639639854431},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5708708763122559},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48426908254623413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47663721442222595},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.46542972326278687},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4182016849517822},{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.41534852981567383},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3811473548412323},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.30516648292541504},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18268737196922302},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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":1,"locations":[{"id":"doi:10.1109/fskd.2014.6980856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2014.6980856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1493217831","https://openalex.org/W1544139368","https://openalex.org/W1593486402","https://openalex.org/W1641039719","https://openalex.org/W1989921625","https://openalex.org/W2003639310","https://openalex.org/W2058815042","https://openalex.org/W2068383400","https://openalex.org/W2103202420","https://openalex.org/W2132117751","https://openalex.org/W2138612638","https://openalex.org/W2143065952","https://openalex.org/W2144544802","https://openalex.org/W2147694185","https://openalex.org/W2168846334","https://openalex.org/W2337480916","https://openalex.org/W4285719527","https://openalex.org/W6629329278","https://openalex.org/W6635743399","https://openalex.org/W6682094280"],"related_works":["https://openalex.org/W25732909","https://openalex.org/W4323338832","https://openalex.org/W4289596129","https://openalex.org/W170643605","https://openalex.org/W1999879627","https://openalex.org/W4295189757","https://openalex.org/W2088055539","https://openalex.org/W1574834681","https://openalex.org/W2389167168","https://openalex.org/W2170721049"],"abstract_inverted_index":{"As":[0],"an":[1,180],"effective":[2,181],"biclustering":[3],"model,":[4],"order-preserving":[5],"submatrix":[6],"(OPSM)":[7],"has":[8],"been":[9,118],"widely":[10],"applied":[11],"to":[12,21,183],"biological":[13,49],"gene":[14,42],"expression":[15],"data":[16,125],"mining.":[17],"Recently,":[18],"biologists":[19],"hope":[20],"find":[22,150],"deep":[23,66,86,98,104,141,153,186],"OPSMs":[24,105,142,154],"with":[25,64,143,155,163],"long":[26],"patterns":[27],"and":[28,81,123,127],"comparatively":[29],"few":[30],"support":[31,76,158,175],"rows,":[32],"which":[33,100,147,170],"are":[34],"not":[35,62],"only":[36],"useful":[37],"on":[38,58,172],"the":[39,52,65,103,108,128,137,152,164,185],"interpretation":[40],"of":[41,140,160],"regulatory":[43],"networks":[44],"but":[45],"also":[46],"have":[47,117],"essential":[48],"significance.":[50],"Unfortunately,":[51],"traditional":[53,165],"exact":[54,94],"mining":[55,97,139,168],"algorithms":[56,169],"based":[57],"Apriori":[59],"principle":[60],"could":[61,148],"deal":[63],"OPSM":[67,187],"problem,":[68],"since":[69],"they":[70],"often":[71],"take":[72],"a":[73,92,144,156],"large":[74,174],"minimum":[75,157],"threshold":[77,159],"for":[78,96,136],"pattern":[79,167],"pruning,":[80],"inevitably":[82],"miss":[83],"some":[84],"significant":[85],"OPSMs.":[87],"Therefore,":[88],"this":[89],"paper":[90],"proposes":[91],"new":[93],"algorithm":[95,133,178],"OPSMs,":[99],"obtain":[101],"all":[102,151],"by":[106,112],"finding":[107],"common":[109],"subsequences":[110],"shared":[111],"every":[113],"two":[114],"rows.":[115],"Experiments":[116],"done":[119],"in":[120],"both":[121],"real":[122],"synthetic":[124],"sets,":[126],"results":[129],"show":[130],"that":[131],"our":[132,177],"is":[134,179],"suitable":[135],"full":[138],"small":[145],"support,":[146],"even":[149],"2.":[161],"Compared":[162],"sequential":[166],"depend":[171],"relatively":[173],"threshold,":[176],"one":[182],"solve":[184],"problem.":[188]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
