Prepoznavanje žaljivih objav z metodami strojnega učenja

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Language:	Slovenian
Year of publishing:	2013
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[L. N. Jovan]
UDC:	004.8(043.2)
COBISS:	10132564
Views:	74
Downloads:	5
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Secondary language:	English
Secondary title:	Detecting offensive posts with machine learning methods
Secondary abstract:	The main goal of this thesis was to develop a recognition system for offensive posts on the web. Theoretical backgrounds of machine learning, text mining and text categorization approaches are given for better understanding of this field of computer science. We present a framework of such a system, from text pre-processing, feature selection, term weighting to selection of best classifiers. The results are tested using the data obtained from a related competition on Kaggle. For the purpose of the thesis a database of Slovenian comments was built, which serves as a data set to verify the success of the classification of offensive comments in Slovenian language.
Secondary keywords:	machine learning;text mining;classification;offensive posts;computer science;computer and information science;diploma;
File type:	application/pdf
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univerza v Ljubljani, Fak. za računalništvo in informatiko
Pages:	65 str.
ID:	24207397