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Title:Ogrodje za samodejno načrtovanje športnih aktivnosti : magistrsko delo
Authors:ID Koprivc, Luka (Author)
ID Fister, Iztok (Mentor) More about this mentor... New window
ID Vrbančič, Grega (Comentor)
Files:.pdf MAG_Koprivc_Luka_2023.pdf (4,30 MB)
MD5: 5C6D93A29D73A5D8DC0C815A36D31761
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V dobi obilice podatkov se pred nami razprostira bogat nabor informacij in naprednih metod zajemanja. Med temi izstopajo zabeleženi podatki o športnih aktivnostih, ki odpirajo vrata analizi in vizualizaciji, vendar še vedno ohranjajo omejitve pri manipulaciji. V okviru te magistrske naloge je predstavljeno inovativno ogrodje, ki izrabi obstoječe aktivnosti in s pomočjo usmerjenih grafov inteligentno predlaga potek nove športne dejavnosti. V začetku se temeljito posvetimo izzivom področja ter preučimo relevantne raziskave. Sledi podrobna razlaga algoritmov, ki omogočajo učinkovito obvladovanje kompleksnosti problema, hkrati pa predstavimo tudi algoritme za obdelavo samoizmerjenih aktivnosti. Zaključimo s praktično uporabo razvitega ogrodja ter podamo refleksijo o njegovi učinkovitosti in koristnosti.
Keywords:obdelava podatkov, podatkovna znanost, python, športne aktivnosti
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[L. Koprivc]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (X, 43 f.))
PID:20.500.12556/DKUM-85272 New window
UDC:004.62.021(043.2)
COBISS.SI-ID:174214659 New window
Publication date in DKUM:12.10.2023
Views:585
Downloads:53
Metadata:XML 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:24.08.2023

Secondary language

Language:English
Title:Framework for automated sports activity planning
Abstract:In the era of data, more data and data recording methods exist than ever before. Recorded sports activities data are a newer field of study, and can be used for analysis and visualization. However, the possibilities for their manipulation remain very limited. This thesis presents a solution which uses existing activities and directed graphs to recommend paths of new activities. Firstly, we present this work`s field of research and research similar works. Secondly, we propose a solution which we present thoroughly. We present the algorithms which allow us to manage the solution`s complexity and algorithms for processing the activities. Finally, we present the usage of our solution and share our thoughts on its implementation.
Keywords:data processing, data science, python, sports activities


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