Text data mining as an viable method of Japanese studies
| Thesis title in Czech: | Data mining jako metoda použitelná v oblasti japonských studií |
|---|---|
| Thesis title in English: | Text data mining as an viable method of Japanese studies |
| Key words: | data mining|japonská studia|metodologie |
| English key words: | data mining|Japanese studies|methodology |
| Academic year of topic announcement: | 2017/2018 |
| Thesis type: | Bachelor's thesis |
| Thesis language: | angličtina |
| Department: | Department of Sinology (21-KSI) |
| Supervisor: | Mgr. Petra Kanasugi, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 10.09.2018 |
| Date of assignment: | 10.09.2018 |
| Administrator's approval: | not processed yet |
| Confirmed by Study dept. on: | 18.09.2018 |
| Date and time of defence: | 18.06.2019 09:00 |
| Date of electronic submission: | 09.05.2019 |
| Date of proceeded defence: | 18.06.2019 |
| Submitted/finalized: | committed by student and finalized |
| Opponents: | Ing. Alexandr Rosen, Ph.D. |
| Guidelines |
| 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. |
| References |
| 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 |