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Title:
Podatkovno podprta evalvacija znanj in spretnosti : magistrsko delo
Authors:
ID
Robnik, Damijan
(
Author
)
ID
Karakatič, Sašo
(
Mentor
)
More about this mentor...
Files:
MAG_Robnik_Damijan_2023.pdf
(7,14 MB)
MD5: 6CD1F92B1B4AC104E08E9B305610219E
Language:
Slovenian
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Magistrsko delo opisuje uporabo algoritma Node2Vec za analizo odnosov med strokovnjaki in njihovimi izkušnjami na področju informacijske tehnologije (IT). V delu je predstavljen algoritem za generiranje simuliranih izkušenj strokovnjakov, ki se uporabi za ustvarjanje grafa kot vhod v Node2Vec. Prav tako so predstavljeni rezultati ankete, s katero smo pridobili potrebne podatke o izkušnjah strokovnjakov na področju IT. Na podlagi teh podatkov in simuliranih izkušenj je ocenjena uspešnost algoritma Node2Vec pri razvrščanju spletnih programerjev v skupine (gruče).
Keywords:
IT znanja
,
teorija grafov
,
nevronske mreže
,
Node2Vec
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[D. Robnik]
Year of publishing:
2023
Number of pages:
1 spletni vir (1 datoteka PDF (XII, 123 f.))
PID:
20.500.12556/DKUM-84995
UDC:
004.032.26:519.17(043.2)
COBISS.SI-ID:
176855811
Publication date in DKUM:
12.10.2023
Views:
574
Downloads:
73
Metadata:
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:
14.08.2023
Secondary language
Language:
English
Title:
Data supported evaluation of knowledge and skills
Abstract:
The master's thesis describes the application of the Node2Vec algorithm for analyzing the relationships between experts and their experiences in the field of information technology (IT). The thesis presents an algorithm for generating simulated expert experiences, which are used to create a graph as input to Node2Vec. Additionally, the results of a survey are presented, which provides the necessary data on experts' experiences in the IT domain. Based on this data and the simulated experiences, the performance of the Node2Vec algorithm in clustering web programmers into common clusters is evaluated.
Keywords:
IT skills
,
graph theory
,
neural networks
,
Node2Vec
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