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Title:Interaktivna vizualizacijska orodja za izboljševanje športnih treningov : magistrsko delo
Authors:ID Šuster, Roman (Author)
ID Fister, Iztok (Mentor) More about this mentor... New window
Files:.pdf MAG_Suster_Roman_2020.pdf (5,91 MB)
MD5: F3C6229254024468A4F7195D6199B7B3
PID: 20.500.12556/dkum/536110ca-7ece-4fb2-8b5e-9c5429bbcfa4
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Vsakodnevno se soočamo z veliko količino podatkov, ki jih generirajo elektronske naprave. Še več, ta količina se z dneva v dan celo povečuje in temu povečevanju ni videti konca. Vseprisotne elektronske naprave so korenito spremenile tudi življenje človeka. Med drugim te naprave beležijo naše odločitve, na podlagi katerih določajo naše preference, spremljajo naše nakupovalne navade v trgovinah, odkrivajo naše finančne navade in obnašanje na družbenih omrežjih. Zaradi vsega prej omenjenega so se razvile metode, ki omogočajo shranjevanje in obdelavo velike količine podatkov, ki jih danes označujemo z izrazom masivni podatki (angl. big data). V pričujočem magistrskem delu smo se lotili obdelave podatkov športnikov (natančneje kolesarjev) dobljenih iz športnih ur (npr. Polar, Garmin ipd.), ki spremljajo športnika med treningi. Na podlagi te analize lahko športni trener določi trende v obnašanju športnika znotraj predpisanih časovnih intervalov, na podlagi česar lahko ta ugotavlja, v kakšni trenutni formi je njegov varovanec in napovedati priporočila za njegov nadaljnji trening.
Keywords:podatkovno rudarjenje, analiza podatkov, vizualizacija, šport, spletna aplikacija
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[R. Šuster]
Year of publishing:2020
Number of pages:XI, 55 f.
PID:20.500.12556/DKUM-76795 New window
UDC:004.6:004.9(043.2)
COBISS.SI-ID:40423683 New window
NUK URN:URN:SI:UM:DK:WMHPDKMK
Publication date in DKUM:04.11.2020
Views:978
Downloads:63
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:08.07.2020

Secondary language

Language:English
Title:Interactive visualization tools for improving sports training
Abstract:Nowadays we encounter large amount of data generated by electronic devices on a daily basis. This amount is increasing day by day and there seems to be no end to this increase. Ubiquitous electronic devices have also radically changed human life. Among other things, these devices record our decisions, based on which they determine our preferences, monitor our shopping habits in stores, discover our financial habits and behavior on social networks. Due to all of the above, methods have been developed that allow the storage and processing of large amounts of data, which today are referred to as big data. In this master's thesis, we started processing the data of athletes (more precisely cyclists) obtained from sports devices (e.g. Polar, Garmin, etc.) that accompany the athlete during training. Based on this analysis, the sports coach can determine trends in the athlete's behavior within the prescribed time intervals, on the basis of which he can determine the current form of his client and predict recommendations for his further training.
Keywords:data mining, data analysis, visualization, sports, web application


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