{"id":"https://openalex.org/W2793606024","doi":"https://doi.org/10.5334/dsj-2018-006","title":"Shapelet Classification Algorithm Based on Efficient Subsequence Matching","display_name":"Shapelet Classification Algorithm Based on Efficient Subsequence Matching","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2793606024","doi":"https://doi.org/10.5334/dsj-2018-006","mag":"2793606024"},"language":"en","primary_location":{"id":"doi:10.5334/dsj-2018-006","is_oa":true,"landing_page_url":"https://doi.org/10.5334/dsj-2018-006","pdf_url":"http://datascience.codata.org/articles/10.5334/dsj-2018-006/galley/743/download/","source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"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 Science Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://datascience.codata.org/articles/10.5334/dsj-2018-006/galley/743/download/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101815036","display_name":"Huiqing Wang","orcid":"https://orcid.org/0000-0001-8611-6546"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huiqing Wang","raw_affiliation_strings":["Taiyuan University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371573","display_name":"Chun Li","orcid":"https://orcid.org/0000-0003-2311-3422"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Li","raw_affiliation_strings":["Taiyuan University of Technology"],"raw_orcid":"https://orcid.org/0000-0003-2311-3422","affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101907683","display_name":"Hongwei Sun","orcid":"https://orcid.org/0009-0000-3663-0723"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongwei Sun","raw_affiliation_strings":["Taiyuan University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101778700","display_name":"Zhirong Guo","orcid":"https://orcid.org/0000-0002-6660-7142"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhirong Guo","raw_affiliation_strings":["Taiyuan University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000367080","display_name":"Yingying Bai","orcid":"https://orcid.org/0000-0003-1492-3597"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingying Bai","raw_affiliation_strings":["Taiyuan University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Taiyuan University of Technology","institution_ids":["https://openalex.org/I9086337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101815036"],"corresponding_institution_ids":["https://openalex.org/I9086337"],"apc_list":{"value":350,"currency":"GBP","value_usd":429},"apc_paid":{"value":350,"currency":"GBP","value_usd":429},"fwci":0.1656,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.41526141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"17","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9599000215530396,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10750","display_name":"Fermentation and Sensory Analysis","score":0.9031000137329102,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subsequence","display_name":"Subsequence","score":0.7637159824371338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6965502500534058},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5854196548461914},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5722949504852295},{"id":"https://openalex.org/keywords/longest-common-subsequence-problem","display_name":"Longest common subsequence problem","score":0.5330668091773987},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.4781951904296875},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46478721499443054},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4639752507209778},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46268430352211},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4613950252532959},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.44283509254455566},{"id":"https://openalex.org/keywords/blossom-algorithm","display_name":"Blossom algorithm","score":0.4263668656349182},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.42082899808883667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3776973485946655},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33890610933303833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30747824907302856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1851222813129425},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.06135505437850952}],"concepts":[{"id":"https://openalex.org/C137877099","wikidata":"https://www.wikidata.org/wiki/Q1332977","display_name":"Subsequence","level":3,"score":0.7637159824371338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6965502500534058},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5854196548461914},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5722949504852295},{"id":"https://openalex.org/C120098539","wikidata":"https://www.wikidata.org/wiki/Q141001","display_name":"Longest common subsequence problem","level":2,"score":0.5330668091773987},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.4781951904296875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46478721499443054},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4639752507209778},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46268430352211},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4613950252532959},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.44283509254455566},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.4263668656349182},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.42082899808883667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3776973485946655},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33890610933303833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30747824907302856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1851222813129425},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.06135505437850952},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.5334/dsj-2018-006","is_oa":true,"landing_page_url":"https://doi.org/10.5334/dsj-2018-006","pdf_url":"http://datascience.codata.org/articles/10.5334/dsj-2018-006/galley/743/download/","source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"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 Science Journal","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a13d3f9f51bd4d70a07c41512d7fec97","is_oa":true,"landing_page_url":"https://doaj.org/article/a13d3f9f51bd4d70a07c41512d7fec97","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Science Journal, Vol 17 (2018)","raw_type":"article"},{"id":"pmh:oai:ojs.datascience.codata.org:article/752","is_oa":true,"landing_page_url":"https://datascience.codata.org/jms/article/view/dsj-2018-006","pdf_url":null,"source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Science Journal; Vol 17 (2018); 6","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.5334/dsj-2018-006","is_oa":true,"landing_page_url":"https://doi.org/10.5334/dsj-2018-006","pdf_url":"http://datascience.codata.org/articles/10.5334/dsj-2018-006/galley/743/download/","source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"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 Science Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2793606024.pdf","grobid_xml":"https://content.openalex.org/works/W2793606024.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1738313275","https://openalex.org/W1778796894","https://openalex.org/W1973565866","https://openalex.org/W1984674851","https://openalex.org/W1989417520","https://openalex.org/W2008348094","https://openalex.org/W2027096757","https://openalex.org/W2030863907","https://openalex.org/W2032710952","https://openalex.org/W2058220737","https://openalex.org/W2081028405","https://openalex.org/W2098759488","https://openalex.org/W2099302229","https://openalex.org/W2108917412","https://openalex.org/W2123502857","https://openalex.org/W2146291192","https://openalex.org/W2149945051","https://openalex.org/W2166547175","https://openalex.org/W2400311702","https://openalex.org/W2402972623","https://openalex.org/W2954016381"],"related_works":["https://openalex.org/W25732909","https://openalex.org/W4323338832","https://openalex.org/W4289596129","https://openalex.org/W3083981518","https://openalex.org/W4225868058","https://openalex.org/W1999879627","https://openalex.org/W2088055539","https://openalex.org/W1574834681","https://openalex.org/W2389167168","https://openalex.org/W1746697883"],"abstract_inverted_index":{"<p":[0],"class=\"p1\">Shapelet":[1],"classification":[2,7,48,56,86,135,144,154],"algorithms":[3],"are":[4,17],"an":[5,41],"accurate":[6],"method":[8],"for":[9,46,71,108],"time":[10,94],"series":[11,61,95],"data.":[12],"Existing":[13],"shapelet":[14,47,54,134],"classifying":[15],"processes":[16],"relatively":[18,142],"inefficient":[19],"and":[20,40,75,100,105,110,114,152],"slow":[21],"due":[22],"to":[23,82],"the":[24,50,64,68,84,103,112,117,124,133,137,148],"large":[25],"amount":[26],"of":[27,116],"necessary":[28],"complex":[29],"distance":[30],"computations.":[31],"This":[32],"paper":[33,51],"therefore":[34],"introduces":[35],"piecewise":[36],"aggregate":[37],"approximation(PAA)":[38],"representation":[39,70],"efficient":[42,60,125],"subsequence":[43,79,126],"matching":[44,80,127],"algorithm":[45,57,66,81,107,128,139,149],"algorithms;":[49],"also":[52],"proposes":[53],"transformation":[55],"based":[58],"on":[59,91],"matching.":[62],"First,":[63],"proposed":[65],"took":[67],"PAA":[69],"appropriate":[72],"dimension":[73],"reduction,":[74],"then":[76],"used":[77,102],"a":[78],"simplify":[83],"data":[85],"process.":[87],"The":[88],"research":[89],"experimented":[90],"14":[92],"public":[93],"datasets":[96],"taken":[97],"from":[98],"UCI":[99],"UCR,":[101],"original":[104],"new":[106,138],"classification,":[109],"compared":[111],"efficiency":[113],"accuracy":[115],"two":[118],"methods.":[119],"Experimental":[120],"results":[121],"showed":[122],"that":[123],"could":[129,140],"be":[130],"combined":[131],"with":[132],"algorithm;":[136],"ensure":[141],"high":[143],"accuracy,":[145],"effectively":[146],"simplified":[147],"calculation":[150],"process,":[151],"improved":[153],"efficiency.":[155]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}