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Title:Priporočilni sistem in mobilna aplikacija za ustvarjanje fitnes treninga
Authors:ID Zajc, Dejan (Author)
ID Ojsteršek, Milan (Mentor) More about this mentor... New window
ID Borovič, Mladen (Comentor)
Files:.pdf UN_Zajc_Dejan_2018.pdf (1,70 MB)
MD5: 0FA013D0A37630A939AADA392ACB2BE4
PID: 20.500.12556/dkum/56f27d16-4a07-442e-9a09-666ef32d5a52
 
Language:Slovenian
Work type:Bachelor thesis/paper
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Priporočilni sistemi se zaradi velikega števila informacij vedno bolj uveljavljajo. Enako velja na fitnes področju, kjer ljudje nimajo časa, denarja ali motivacije za obisk fitnes centrov. V diplomskem delu predstavimo priporočilni sistem za ustvarjanje fitnes treninga. Pri tem uporabimo vsebinsko priporočanje. Uporabo priporočilnega sistema omogočimo z implementacijo spletne storitve, ki jo kličemo v mobilni aplikaciji. V teoretičnem delu opišemo uporabljen pristop vsebinskega priporočanja in samo logiko priporočanja. V praktičnem delu implementiramo spletno storitev in mobilno aplikacijo.
Keywords:priporočilni sistem, vsebinsko priporočanje, hibridna mobilna aplikacija, Ionic
Place of publishing:Maribor
Year of publishing:2018
PID:20.500.12556/DKUM-72673 New window
NUK URN:URN:SI:UM:DK:AZNR4YM4
Publication date in DKUM:26.08.2020
Views:1713
Downloads:176
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:12.10.2018

Secondary language

Language:English
Title:Recommender system and a mobile application for creating fitness training
Abstract:Recommender systems are increasingly becoming popular due to large amounts of information produced. In fitness, they can be used since some people do not find time, money or motivation to visit fitness centers. In this thesis, we present a recommender system for fitness training. We use a content-based recommendation technique. The recommender system is implemented with a web service and its use is demonstrated with a mobile application. In the theoretical part, we describe the used content-based approach to recommendation and the recommendation logic. In the practical part, we implement the web service and the mobile application.
Keywords:recommender system, content-based recommendation, hybrid mobile application, Ionic


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