Text classification with artificial neural networks – Bc. Anouk Wilstra
Bc. Anouk Wilstra
Bachelor's thesis
Text classification with artificial neural networks
Text classification with artificial neural networks
Abstract:
Umělé neuronové sítě umožňují modelování komplexnějších problémů včetně zpracování přirozeného jazyka. Schopnost počítačů číst a rozumět textu napsaného člověkem je v době big data a umělé inteligence kritickou a velmi zkoumanou oblastí. Tato práce se věnuje využití neuronových sítí pro profilování autorů, konkrétně klasifikaci textu do tří kategorií věku autorů. Pro vytvoření celé řady modelů je využito …moreAbstract:
Artificial neural networks allow for the modelling of more complex problems, including natural language processing. The ability for computers to read and understand human written text is critical in the age of big data and artificial intelligence, and it is heavily researched. This thesis uses neural networks for author profiling, classifying texts into three author age categories. Three different …more
Language used: English
Date on which the thesis was submitted / produced: 15. 8. 2022
Identifier:
http://evskp.uhk.cz/eB13903
Thesis defence
- Date of defence: 8. 9. 2022
- Supervisor: Ing. Milan Košťák
- Reader: Ing. Karel Mls, Ph.D.
Citation record
ISO 690-compliant citation record:
WILSTRA, Anouk. \textit{Text classification with artificial neural networks}. Online. Bachelor's thesis. Hradec Králové: University of Hradec Králové, Faculty of Informatics and Management. 2022. Available from: https://theses.cz/id/tykl65/.
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- Soubory jsou od 27. 9. 2022 dostupné: světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Univerzita Hradec KrálovéUniversity of Hradec Králové
Faculty of Informatics and ManagementBachelor programme / field:
Aplikovaná informatika / Aplikovaná informatika
Theses on a related topic
-
Explaining convolutional neural network using clustering methods
Adam Bajger -
Comparison of methods for clustering convolutional neural network intercomputation values with respect to explainability
Adrián Bindas -
Modelling small-RNA binding using Convolutional Neural Networks
Eva Klimentová -
implement classification for traffic signs using convolutional neural network
Mohamad Abdulrahman -
Practical use of natural language processing in education technology
Dominik Hartinger -
Application of Natural language processing to enhance qualitative research used for marketing
Poj Nuangniyom Netsiri -
Scalability of Semantic Analysis in Natural Language Processing
Radim Řehůřek -
Artificial Neural Networks in Space of Stock Returns: Volatility Prediction
Šimon Škorňa
Name
Posted by
Uploaded/Created
Rights
Folders
Files
Kohout, J.
28/9/2022
Kohout, J.
28/9/2022