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Title:Razvoj modela za podporo odločanja na področju duševnega zdravja : magistrska naloga
Authors:ID Kovačevič Rudolf, Daniel (Author)
ID Mertik, Matej (Mentor) More about this mentor... New window
Files:.pdf MAG_2014_Daniel_Kovacevic_Rudolf.pdf (2,19 MB)
MD5: 993685479210415D89B49E0B6FAB1C65
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FIŠ - Faculty of Information Studies in Novo mesto
Abstract:V magistrski nalogi razpravljamo o tekstovnem rudarjenju, ki je proces podatkovnega rudarjenja, razvitega kot znanstveni pristop iz strojnega učenja in statistike. V nalogi obravnavamo raziskovalni problem pridobivanja uporabnega znanja iz nestrukturiranih besedilnih virov za namen področja diagnostike na področju medicine, natančneje na področju duševnega zdravja. V nalogi najprej opišemo področje rudarjenja nad besedili, t. i. tekstovno rudarjenje, in nekaj poglavitnih metod, predstavimo domeno diagnostike in izzive na področju duševnega zdravja in na podlagi metodologije, ki smo jo v ta namen razvili, pripravimo model nad pridobljenimi podatki iz besedilnih virov, kar je namenjeno podpori odločanju v medicini. Magistrska naloga raziskuje, ali je pridobivanje informacij iz besedilnih virov s pomoĉjo tekstovnega rudarjenja primerno kot orodje za pomoč pri diagnostiki v medicini.
Keywords:podatkovno rudarjenje, tekstovno rudarjenje, diagnoza, podpora pri odločanju
Place of publishing:Novo mesto
Place of performance:Novo mesto
Publisher:[D. Kovačevič Rudolf]
Year of publishing:2014
Year of performance:2014
Number of pages:88 str., [26] str. pril.
PID:20.500.12556/ReVIS-4713 New window
COBISS.SI-ID:2048276243 New window
UDC:004.8(043.2)
Note:Na ov.: Magistrska naloga : študijskega programa druge stopnje;
Publication date in ReVIS:10.08.2018
Views:4319
Downloads:141
Metadata:XML DC-XML DC-RDF
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KOVAČEVIČ RUDOLF, Daniel, 2014, Razvoj modela za podporo odločanja na področju duševnega zdravja : magistrska naloga [online]. Master’s thesis. Novo mesto : D. Kovačevič Rudolf. [Accessed 27 March 2025]. Retrieved from: https://revis.openscience.si/IzpisGradiva.php?lang=eng&id=4713
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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:10.08.2018

Secondary language

Language:English
Abstract:In the thesis we discuss text mining as the process of data mining developed by scientific approach of machine learning and statistics. The thesis research dealt with the problem of extracting useful knowledge from unstructured text sources for the purpose of the diagnosis in the medical field, specifically in the field of mental health. The paper first describe the mining of texts, so-called text mining, and some of the main methods to present the domain of diagnosis and challenges in the field of mental health and on the basis of the methodology that we have developed, we have prepared a model of the data acquired from text sources, which is designed to support decision-making in medicine. Master's thesis explores the extraction of information from textual sources using text mining tools as appropriate to assist in the medicine diagnosis.
Keywords:data mining, text mining, diagnose, decision support


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