- author = "Lukas Povoda",
- title = "Text Mining Based on Artificial Intelligence Methods",
- school = "Faculty of Electrical Engineering and Communication, Brno University of Technology",
- year = "2018",
- address = "Purkynova 118, CZ-61200 Brno, Czech Republic",
- month = "14 " # dec,
- keywords = "genetic algorithms, genetic programming, Artificial intelligence, data mining, emotion classification, genetic programming optimization, natural language processing, sentiment analysis, text data, text mining",
-
URL = "
https://www.vutbr.cz/en/students/final-thesis?zp_id=113382",
-
URL = "https://www.vutbr.cz/www_base/zav_prace_soubor_verejne.php?file_id=178003",
- size = "101 pages",
- abstract = "This work deals with the problem of text mining which is becoming more popular due to exponential growth of the data in electronic form. The work explores contemporary methods and their improvement using optimization methods, as well as the problem of text data understanding in general. The work addresses the problem in three ways: using traditional methods and their optimizations, using Big Data in train phase and abstraction through the minimization of language-dependent parts, and introduction of the new method based on the deep learning which is closer to how human reads and understands text data. The main aim of the dissertation was to propose a method for machine understanding of unstructured text data. The method was experimentally verified by classification of text data on 5 different languages: Czech, English, German, Spanish and Chinese. This demonstrates possible application to different languages families. Validation on the Yelp evaluation database achieve accuracy higher by 0.5% than current methods.",
-
notes = "Language of thesis: Slovak
Supervisor: doc. Ing. Radim Burget",
