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Title:Uporaba javno dostopnih podatkov za oceno podobnosti vozil z ukradenimi : diplomsko delo visokošolskega študijskega programa Informacijska varnost
Authors:ID Steiner, Benjamin (Author)
ID Vrhovec, Simon (Mentor) More about this mentor... New window
Files:.pdf VS_Steiner_Benjamin_2021.pdf (1,06 MB)
MD5: A223FBEC1C8F32F28882325D2E9BFB3E
PID: 20.500.12556/dkum/f8dc6cb2-d760-4d17-9c9e-16c8180b586c
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FVV - Faculty of Criminal Justice and Security
Abstract:V Sloveniji je letno ukradenih med 900 in 1100 vozil, ampak policiji uspe izslediti le 25% teh vozil. Trenutno ne obstaja storitev, preko katere lahko poljubno vozilo primerjamo s seznamom ukradenih vozil in izluščimo le najbolj podobna vozila, ali posledično najdemo ukradeno vozilo. Za naslovitev problema je bil ustvarjen model, ki s pomočjo uporabe algoritma za iskanje najbližjih sosedov išče ukradena vozila, ki so najbolj podobna poljubno izbranemu vozilu. Da bi testirali razviti model, smo izbrali 200 vozil za vsako izmed 11 najpogostejših znamk avtomobilov na spletni strani Avto.net. Razdalje med avtomobili smo razvrstili v 3 opisne stopnje glede na podobnost: zelo podobna vozila, podobna vozila in malo podobna vozila. Opisne stopnje podobnosti so ustrezno merilo za ocenjevanje podobnosti vozil, saj so mejne razdalje med vozili jasno določene in neodvisne od znamke avtomobilov.
Keywords:podatki, javno dostopni podatki, rudarjenje podatkov, ukradena vozila, diplomske naloge
Place of publishing:Ljubljana
Place of performance:Ljubljana
Publisher:[B. Steiner]
Year of publishing:2021
Year of performance:2021
Number of pages:VI f., 27 str.
PID:20.500.12556/DKUM-80158 New window
UDC:004.8(043.2)
COBISS.SI-ID:85463299 New window
Publication date in DKUM:18.11.2021
Views:1090
Downloads:92
Metadata:XML DC-XML DC-RDF
Categories:FVV
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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:31.08.2021

Secondary language

Language:English
Title:Use of publicly available data to assess the similarity of vehicles with stolen ones
Abstract:In Slovenia, between 900 and 1100 vehicles are stolen every year, but the police only manage to recover about 25% of the stolen vehicles. Currently, there is no service that enables a comparison between the selected and the stolen vehicle and extracts only the most similar vehicles, or consequently finds the stolen vehicle. To solve this problem, a model was created. In the model, we used Nearest Neighbours algorithm to search for stolen vehicles that are most similar to the selected vehicle. To test the developed model, we selected 200 vehicles for each of the 11 most popular car brands on the Avto.net website. The distances between vehicles were classified into 3 descriptive levels depending on their similarity: very similar vehicles, similar vehicles, and slightly similar vehicles. Descriptive similarity levels are a suitable criterion for assessing vehicle similarity because the distances between vehicles are clearly defined and independent of car brand.
Keywords:Python, Orange, stolen vehicles, finding nearest neighbours


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