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Title:Priporočilni sistem in mobilna aplikacija za ustvarjanje fitnes treninga
Authors:Zajc, Dejan (Author)
Ojsteršek, Milan (Mentor) More about this mentor... New window
Borovič, Mladen (Co-mentor)
Files:.pdf UN_Zajc_Dejan_2018.pdf (1,70 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
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
Year of publishing:2018
Source:Maribor
NUK URN:URN:SI:UM:DK:AZNR4YM4
License:CC BY-NC-ND 4.0
This work is available under this license: Creative Commons Attribution Non-Commercial No Derivatives 4.0 International
Views:395
Downloads:91
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Categories:KTFMB - FERI
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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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