{"id":"https://openalex.org/W4385484920","doi":"https://doi.org/10.1109/icphm57936.2023.10194224","title":"An Entropy-based Data Reduction Method for Data Preprocessing","display_name":"An Entropy-based Data Reduction Method for Data Preprocessing","publication_year":2023,"publication_date":"2023-06-05","ids":{"openalex":"https://openalex.org/W4385484920","doi":"https://doi.org/10.1109/icphm57936.2023.10194224"},"language":"en","primary_location":{"id":"doi:10.1109/icphm57936.2023.10194224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm57936.2023.10194224","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Prognostics and Health Management (ICPHM)","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/A5092581671","display_name":"Rocco Cassandro","orcid":"https://orcid.org/0009-0004-5087-2226"},"institutions":[{"id":"https://openalex.org/I19833938","display_name":"Western New England University","ror":"https://ror.org/007cnf143","country_code":"US","type":"education","lineage":["https://openalex.org/I19833938"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rocco Cassandro","raw_affiliation_strings":["Western New England University,Department of Industrial Engineering and Engineering Management,Springfield,MA,USA,01119"],"affiliations":[{"raw_affiliation_string":"Western New England University,Department of Industrial Engineering and Engineering Management,Springfield,MA,USA,01119","institution_ids":["https://openalex.org/I19833938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070515481","display_name":"Quing Li","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quing Li","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China,Chengdu,China,611731"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China,Chengdu,China,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100696183","display_name":"Zhaojun Li","orcid":"https://orcid.org/0000-0002-2755-7592"},"institutions":[{"id":"https://openalex.org/I19833938","display_name":"Western New England University","ror":"https://ror.org/007cnf143","country_code":"US","type":"education","lineage":["https://openalex.org/I19833938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaojun Steven Li","raw_affiliation_strings":["Western New England University,Department of Industrial Engineering and Engineering Management,Springfield,MA,USA,01119"],"affiliations":[{"raw_affiliation_string":"Western New England University,Department of Industrial Engineering and Engineering Management,Springfield,MA,USA,01119","institution_ids":["https://openalex.org/I19833938"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092581671"],"corresponding_institution_ids":["https://openalex.org/I19833938"],"apc_list":null,"apc_paid":null,"fwci":0.1751,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54463976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"351","last_page":"356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9958999752998352,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9941999912261963,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7891381978988647},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7648977637290955},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.7162342667579651},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7049331665039062},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6693634986877441},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5355131030082703},{"id":"https://openalex.org/keywords/data-reduction","display_name":"Data reduction","score":0.49303361773490906},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.4477437436580658},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44164618849754333},{"id":"https://openalex.org/keywords/usability","display_name":"Usability","score":0.41423389315605164},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3603426218032837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3496357202529907},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1045333743095398}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7891381978988647},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7648977637290955},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.7162342667579651},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7049331665039062},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6693634986877441},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5355131030082703},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.49303361773490906},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.4477437436580658},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44164618849754333},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.41423389315605164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3603426218032837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3496357202529907},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1045333743095398},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icphm57936.2023.10194224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm57936.2023.10194224","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Prognostics and Health Management (ICPHM)","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":18,"referenced_works":["https://openalex.org/W575847903","https://openalex.org/W886543236","https://openalex.org/W1473627731","https://openalex.org/W1961147827","https://openalex.org/W2007266727","https://openalex.org/W2013840542","https://openalex.org/W2014419562","https://openalex.org/W2042035594","https://openalex.org/W2067988826","https://openalex.org/W2082131185","https://openalex.org/W2096335861","https://openalex.org/W2135547590","https://openalex.org/W2165835468","https://openalex.org/W2588336250","https://openalex.org/W2949687910","https://openalex.org/W3140993386","https://openalex.org/W4309228596","https://openalex.org/W6641082943"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"The":[0,41,139,160],"primary":[1],"task":[2],"in":[3,146],"data":[4,20,26,37,42,50,58,73,78,114,128,133],"mining":[5,51,74,115],"is":[6,45,141],"to":[7,12,55,90,105,142,156],"find":[8],"potential":[9],"patterns":[10],"or":[11,97],"discover":[13],"hidden":[14],"and":[15,28,93,125],"useful":[16],"knowledge":[17,109],"from":[18],"given":[19],"sets.":[21],"However,":[22],"with":[23,35],"the":[24,31,84,148,165],"increasing":[25],"quantity":[27],"exploding":[29],"complexity,":[30],"capabilities":[32],"of":[33,49,95,150,162,167,172],"dealing":[34],"massive":[36],"becomes":[38],"very":[39],"crucial.":[40],"preprocessing":[43,79,134],"module":[44],"an":[46,126,151],"integral":[47],"part":[48],"procedure,":[52],"which":[53,147],"aims":[54],"optimize":[56],"input":[57],"usability":[59],"for":[60,132],"subsequent":[61],"tasks":[62],"such":[63],"as":[64,69,71,88],"classification,":[65,98],"clustering,":[66],"association":[67],"analysis":[68],"well":[70],"other":[72],"algorithms.":[75,116],"In":[76],"general,":[77],"procedures":[80],"can":[81,103],"effectively":[82],"reduce":[83],"computational":[85],"complexity":[86],"while":[87],"possible":[89],"ensure":[91],"accuracy":[92],"efficiency":[94],"prediction":[96],"but":[99],"meanwhile":[100],"it":[101],"even":[102],"assist":[104],"extract":[106],"some":[107],"unknown":[108],"before":[110],"applying":[111],"more":[112],"advanced":[113],"This":[117],"research":[118],"proposes":[119],"a":[120],"three-patterns":[121],"feature":[122],"variables":[123],"technique":[124],"entropy-based":[127],"reduction":[129],"(EBDR)":[130],"algorithm":[131,169],"based":[135],"on":[136,170],"information":[137],"theory.":[138],"goal":[140],"explore":[143],"high-purity":[144],"subsets":[145],"values":[149],"attribute":[152],"are":[153],"directly":[154],"linked":[155],"specific":[157],"class":[158],"labels.":[159],"results":[161],"experiments":[163],"demonstrate":[164],"efficacy":[166],"EBDR":[168],"datasets":[171],"varying":[173],"sizes.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
