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Title:Zaznavanje sentimenta v novicah z globokimi nevronskimi mrežami : diplomska naloga
Authors:ID Pelicon, Andraž (Author)
ID Kralj Novak, Petra (Mentor) More about this mentor... New window
ID Boshkoska, Biljana Mileva (Comentor)
Files:.pdf VS_2019_Andraz_Pelicon.pdf (1,48 MB)
MD5: C22E84A593B5622B5B7C09319C2CD005
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FIŠ - Faculty of Information Studies in Novo mesto
Abstract:Diplomska naloga se ukvarja z analizo sentimenta v novicah. To področje v zadnjem času pridobiva na priljubljenosti, predvsem v okviru napovedovanja gibanja finančnih trgov, vendar je za slovenski jezik še dokaj slabo raziskano. Za slovenščino sicer obstajajo modeli, osnovani na metodi podpornih vektorjev, vendar ti niso dostopni za javno uporabo. V okviru te raziskave smo zasnovali arhitekturo na osnovi nevronskih mrež, ki za klasifikacijo uporablja kombinacijo samodejno generiranih značilk in TF-IDF obtežitev. Modeli, ki uporabljajo omenjeno arhitekturo, dosegajo primerljive rezultate z že obstoječimi modeli in so sposobni učinkovitega učenja na korpusih v velikosti okrog 10.000 dokumentov. Najuspešnejši model iz raziskave je na voljo kot spletna storitev na naslovu classify.ijs.si.
Keywords:analiza sentimenta, novice, slovenščina, nevronske mreže, globoko učenje
Place of publishing:Novo mesto
Place of performance:Novo mesto
Publisher:[A. Pelicon]
Year of publishing:2019
Year of performance:2019
Number of pages:XI, 51 str.
PID:20.500.12556/ReVIS-6068 New window
COBISS.SI-ID:2048611347 New window
UDC:004.032.26(043.2)
Note:Na ov.: Diplomska naloga : visokošolskega strokovnega študijskega programa prve stopnje;
Publication date in ReVIS:04.10.2019
Views:5175
Downloads:125
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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:04.10.2019

Secondary language

Language:English
Abstract:The present thesis deals with the sentiment analysis of news. This field has recently gained in popularity, especially as a supporting method for stock market prediction, but not much research has yet been done on the news in the Slovenian language. Models based on support vector machines do exist but are not available for public use. We developed a neural network architecture that leverages both automatically generated features and TF-IDF weights for classification of Slovenian news. Models based on this architecture achieve comparable results with existing models and can be successfully trained on datasets of approximately 10,000 documents. Our best performing model is available for public use in the form of a web service on the URL classify.ijs.si.
Keywords:sentiment analysis, news, Slovene, neural networks, deep learning


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