{"id":"https://openalex.org/W4393996148","doi":"https://doi.org/10.1186/s40537-024-00893-x","title":"Computer aided technology based on graph sample and aggregate attention network optimized for soccer teaching and training","display_name":"Computer aided technology based on graph sample and aggregate attention network optimized for soccer teaching and training","publication_year":2024,"publication_date":"2024-04-05","ids":{"openalex":"https://openalex.org/W4393996148","doi":"https://doi.org/10.1186/s40537-024-00893-x"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-024-00893-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00893-x","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00893-x","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00893-x","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102153397","display_name":"Guanghui Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghui Yang","raw_affiliation_strings":["School of Physical Education, Yanshan University, Qinhuangdao, 066004, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physical Education, Yanshan University, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102911796","display_name":"Xinyuan Feng","orcid":"https://orcid.org/0000-0001-7252-5605"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyuan Feng","raw_affiliation_strings":["Liren College, Yanshan University, Qinhuangdao, 066004, Hebei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Liren College, Yanshan University, Qinhuangdao, 066004, Hebei, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102911796"],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":2.5282,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.90290116,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9965000152587891,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9965000152587891,"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/T13804","display_name":"Physical Activity and Education Research","score":0.9643999934196472,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13647","display_name":"AI and Big Data Applications","score":0.9642000198364258,"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":0.8086735010147095},{"id":"https://openalex.org/keywords/computational-science-and-engineering","display_name":"Computational Science and Engineering","score":0.6450574398040771},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5946779251098633},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5897694230079651},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5533270835876465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48548081517219543},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4852152168750763},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4764178991317749},{"id":"https://openalex.org/keywords/computer-aided","display_name":"Computer-aided","score":0.45416882634162903},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.26940539479255676},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08041268587112427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8086735010147095},{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.6450574398040771},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5946779251098633},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5897694230079651},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5533270835876465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48548081517219543},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4852152168750763},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4764178991317749},{"id":"https://openalex.org/C2780727963","wikidata":"https://www.wikidata.org/wiki/Q5157368","display_name":"Computer-aided","level":2,"score":0.45416882634162903},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26940539479255676},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08041268587112427},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-024-00893-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00893-x","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00893-x","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b207eb63045c403a8221954efa9c4af9","is_oa":true,"landing_page_url":"https://doaj.org/article/b207eb63045c403a8221954efa9c4af9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 11, Iss 1, Pp 1-18 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-024-00893-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00893-x","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00893-x","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393996148.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W3040387698","https://openalex.org/W3112346585","https://openalex.org/W3116944216","https://openalex.org/W3119139371","https://openalex.org/W3120892219","https://openalex.org/W3121044936","https://openalex.org/W3143082978","https://openalex.org/W3152160919","https://openalex.org/W3183299832","https://openalex.org/W3195498291","https://openalex.org/W3203966018","https://openalex.org/W3217544650","https://openalex.org/W4205601711","https://openalex.org/W4214853615","https://openalex.org/W4225782931","https://openalex.org/W4226242712","https://openalex.org/W4226414181","https://openalex.org/W4285029663","https://openalex.org/W4293084330","https://openalex.org/W4317037294","https://openalex.org/W4321374865","https://openalex.org/W4361252822","https://openalex.org/W4367301174","https://openalex.org/W4377091458","https://openalex.org/W4378374253","https://openalex.org/W4380987209","https://openalex.org/W4381249209","https://openalex.org/W4384705179","https://openalex.org/W4384923235","https://openalex.org/W4387703376","https://openalex.org/W4390537053","https://openalex.org/W6961783832"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4366179611","https://openalex.org/W2996078371"],"abstract_inverted_index":{"Abstract":[0],"Football":[1,273],"is":[2,38,48,97,151,159,198,209],"the":[3,8,25,32,65,83,101,124,136,149,171,180,183,185,203,206,233,286],"most":[4],"popular":[5],"game":[6],"in":[7,72,200,262,296],"world":[9],"and":[10,20,53,86,94,106,121,164,176,202,224,244,275,282,293],"has":[11,29],"significant":[12],"influence":[13],"on":[14,82,278],"various":[15,73],"aspects":[16],"including":[17],"politics,":[18],"economy":[19],"culture.":[21],"The":[22,109,194,228],"experience":[23],"of":[24,35,69,103,173,182,205],"football":[26,37,45,66,263,287],"developed":[27],"nation":[28],"shown":[30],"that":[31,56,232],"steady":[33],"growth":[34],"youth":[36],"crucial":[39],"for":[40,91,153,169,272,284],"elevating":[41],"a":[42],"nation's":[43],"overall":[44],"proficiency.":[46],"It":[47],"essential":[49],"to":[50,58,63,99],"develop":[51],"techniques":[52,252],"create":[54],"strategies":[55],"adapt":[57],"their":[59],"individual":[60],"physical":[61],"features":[62],"resolve":[64],"players\u2019":[67],"problem":[68],"lacking":[70],"exercise":[71],"topics.":[74],"In":[75],"this":[76],"manuscript,":[77],"Computer":[78,268],"aided":[79,255],"technology":[80],"depending":[81],"Graph":[84,162],"Sample":[85,163],"Aggregate":[87,165],"Attention":[88,166],"Network":[89,167],"Optimized":[90],"Soccer":[92,104,174],"Teaching":[93,175,270,274],"Training":[95,276],"(CAT-GSAAN-STT)":[96],"proposed":[98,110,195,207,234],"improve":[100],"efficiency":[102,204],"teaching":[105,225,256,264],"training":[107,266],"effectively.":[108],"method":[111,197,283],"contains":[112],"four":[113],"stages,":[114],"like":[115,214,253],"data":[116,118,126,138,150],"collection,":[117],"preprocessing,":[119],"prediction":[120,158],"optimization.":[122],"Initially":[123],"input":[125],"are":[127,139,187],"collected":[128,137],"by":[129,141,189],"Microsoft":[130],"Kinect":[131],"V2":[132],"smart":[133],"camera.":[134],"Then":[135],"preprocessed":[140],"using":[142,161,190,290],"Improving":[143],"graph":[144],"collaborative":[145],"filtering.":[146],"After":[147],"preprocessing":[148],"given":[152],"motion":[154],"recognition":[155],"layer":[156],"here":[157],"done":[160],"(GSAAN)":[168],"improving":[170],"effectiveness":[172],"Training.":[177],"To":[178],"enhance":[179],"accuracy":[181,241],"system,":[184],"GSAAN":[186],"optimized":[188],"Artificial":[191],"Rabbits":[192],"Optimization.":[193],"CAT-GSAAN-STT":[196],"executed":[199],"Python":[201],"technique":[208,235],"examined":[210],"with":[211,250,265],"different":[212],"metrics,":[213],"accuracy,":[215],"computation":[216],"time,":[217],"learning":[218],"activity":[219],"analysis,":[220],"student":[221],"performance":[222],"ratio":[223],"evaluation":[226,246],"analysis.":[227],"simulation":[229],"outcomes":[230],"proves":[231],"attains":[236],"provides28.33%,":[237],"31.60%,":[238],"25.63%":[239],"higherRecognition":[240],"and33.67%,":[242],"38.12%":[243],"27.34%lesser":[245],"time":[247],"while":[248],"compared":[249],"existing":[251],"computer":[254],"system":[257],"based":[258],"upon":[259],"artificial":[260,291],"intelligence":[261,292],"(STT-IOT-CATS),":[267],"Aided":[269],"System":[271],"Based":[277],"Video":[279],"Image":[280],"(CAT-STT-VI)":[281],"enhancing":[285],"coaching":[288],"quality":[289],"meta":[294],"verse-empowered":[295],"mobile":[297],"internet":[298],"environment":[299],"(SI-STQ-AI-MIE)":[300],"respectively.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}