Text data mining as an viable method of Japanese studies
| Název práce v češtině: | Data mining jako metoda použitelná v oblasti japonských studií |
|---|---|
| Název v anglickém jazyce: | Text data mining as an viable method of Japanese studies |
| Klíčová slova: | data mining|japonská studia|metodologie |
| Klíčová slova anglicky: | data mining|Japanese studies|methodology |
| Akademický rok vypsání: | 2017/2018 |
| Typ práce: | bakalářská práce |
| Jazyk práce: | angličtina |
| Ústav: | Katedra sinologie (21-KSI) |
| Vedoucí / školitel: | Mgr. Petra Kanasugi, Ph.D. |
| Řešitel: | skrytý - zadáno a potvrzeno stud. odd. |
| Datum přihlášení: | 10.09.2018 |
| Datum zadání: | 10.09.2018 |
| Schválení administrátorem: | zatím neschvalováno |
| Datum potvrzení stud. oddělením: | 18.09.2018 |
| Datum a čas obhajoby: | 18.06.2019 09:00 |
| Datum odevzdání elektronické podoby: | 09.05.2019 |
| Datum proběhlé obhajoby: | 18.06.2019 |
| Odevzdaná/finalizovaná: | odevzdaná studentem a finalizovaná |
| Oponenti: | Ing. Alexandr Rosen, Ph.D. |
| Zásady pro vypracování |
| Japanese studies not unlike other humanities seem to be rather reluctant to take advantage of natural language processing methods in its research. The present thesis aims to demonstrate that one of these methods - text data mining - is a viable research method which can bear interesting results in the field of Japanese studies.
The introduction of the thesis will give a basic overview of how text data mining works and what it can offer. The general account will be complement by three case studies presenting possible applications of text data mining in Japanese studies. The first case study will analyze corpora of individual stages of Japanese proletarian literature in order to ascertain differences among them. The second study will analyze English and Japanese provenience texts regarding Yasukuni shrine its symbolic meaning and the issue of Japanese prime ministers to show differences in ideological approach, reasoning and possibly propaganda strategies. The third study will analyze texts on text data mining to outline the main lines of text data mining discourse. |
| Seznam odborné literatury |
| Mehdi Allahzari, Seyed Amin Pouriyeh, Mehdi Assefi, Saeid Safaei, Elizabeth D. Trippe, Juan B. Gutierrez, Krys Kochut, Text Summarization Techniques: A Brief Survey, International Journal of Advanced Computer Science and Applications, 8(10), 2017
Ramzan Talib, Muhammad Kashif Hanif, Shaeela Ayesha, Fakeeha Fatima, Text Mining: Techniques, Applications and Issues, International Journal of Advanced Computer Science and Applications, 7(11), 2016 Jeffrey L. Solka, Text Data Mining: Theory and Methods, Statistics Surveys, 2, 2008 Dipanjan Das, Andre F. T. Martins, A Survey on Automatic Text Summarization, https://www.cs.cmu.edu/~nasmith/LS2/das-martins.07.pdf |