{"id":"https://openalex.org/W4416313329","doi":"https://doi.org/10.1504/ijcsm.2025.149899","title":"Construction of practical teaching data classification model based on ROF-SSA-LGBM and its application in physical education teaching and management","display_name":"Construction of practical teaching data classification model based on ROF-SSA-LGBM and its application in physical education teaching and management","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416313329","doi":"https://doi.org/10.1504/ijcsm.2025.149899"},"language":"en","primary_location":{"id":"doi:10.1504/ijcsm.2025.149899","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijcsm.2025.149899","pdf_url":null,"source":{"id":"https://openalex.org/S84141356","display_name":"International Journal of Computing Science and Mathematics","issn_l":"1752-5055","issn":["1752-5055","1752-5063"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computing Science and Mathematics","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":null,"display_name":"Xinjiao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101072","display_name":"Shangluo University","ror":"https://ror.org/01a56n213","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210101072"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinjiao Zhang","raw_affiliation_strings":["Department of Physical Education and Research, Shangluo University, Shangluo, 726000, China"],"affiliations":[{"raw_affiliation_string":"Department of Physical Education and Research, Shangluo University, Shangluo, 726000, China","institution_ids":["https://openalex.org/I4210101072"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210101072"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18124598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"2","first_page":"192","last_page":"208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12260","display_name":"Educational Technology and Pedagogy","score":0.1469999998807907,"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/T12260","display_name":"Educational Technology and Pedagogy","score":0.1469999998807907,"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/T13027","display_name":"Applied Advanced Technologies","score":0.04699999839067459,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13567","display_name":"AI and Multimedia in Education","score":0.04650000110268593,"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/classifier","display_name":"Classifier (UML)","score":0.5127999782562256},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4553999900817871},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.43950000405311584},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.4047999978065491},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.3887999951839447},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.37310001254081726},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.3400999903678894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5321000218391418},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5038999915122986},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.43950000405311584},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3986000120639801},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.32429999113082886},{"id":"https://openalex.org/C2777598771","wikidata":"https://www.wikidata.org/wiki/Q5341279","display_name":"Educational data mining","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C71406770","wikidata":"https://www.wikidata.org/wiki/Q243253","display_name":"Physical education","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2687000036239624}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijcsm.2025.149899","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijcsm.2025.149899","pdf_url":null,"source":{"id":"https://openalex.org/S84141356","display_name":"International Journal of Computing Science and Mathematics","issn_l":"1752-5055","issn":["1752-5055","1752-5063"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computing Science and Mathematics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Under":[0],"the":[1,8,59,64,91,113,121,134],"background":[2],"of":[3,10,33,48,66,90,106,130,136],"informatisation,":[4],"to":[5,29,45,63],"better":[6,103],"assist":[7],"management":[9],"practical":[11,34,67],"teaching,":[12],"a":[13],"data":[14],"classification":[15,65,109,118,145],"model":[16,93,115,123],"based":[17],"on":[18,74],"ROF-ISSA-LGBM":[19],"is":[20,27,43,56,102],"proposed.":[21],"Firstly,":[22],"rotation":[23],"forest":[24],"algorithm":[25,41],"(ROF)":[26],"used":[28,57,108,126],"screen":[30],"importance":[31],"features":[32],"teaching":[35,68,140],"dataset.":[36],"Then,":[37],"improved":[38],"sparrow":[39],"search":[40],"(ISSA)":[42],"adopted":[44],"optimise":[46],"hyperparameters":[47],"lightweight":[49],"gradient":[50],"boosting":[51],"machine":[52],"(LGBM).":[53],"Finally,":[54],"ISSA-LGBM":[55],"as":[58],"classifier":[60],"and":[61,76,87,97,142],"applied":[62],"datasets.":[69],"The":[70],"results":[71],"reveal":[72],"that":[73,105],"Haberman":[75],"Iris":[77],"datasets":[78],"with":[79],"smaller":[80],"sample":[81],"sizes,":[82],"average":[83,89],"accuracy,":[84],"macro":[85],"average,":[86],"micro":[88],"constructed":[92,114,122],"reach":[94],"80.96%,":[95],"95.38%":[96],"95.44%,":[98],"respectively,":[99],"its":[100],"performance":[101],"than":[104],"commonly":[107],"models,":[110],"which":[111],"means":[112],"has":[116],"high":[117,144],"accuracy.":[119,146],"Therefore,":[120],"can":[124],"be":[125],"for":[127],"deep":[128],"mining":[129],"potential":[131],"information":[132],"in":[133],"dataset":[135],"physical":[137],"education":[138],"practice":[139],"data,":[141],"shows":[143]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-11-18T00:00:00"}
