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Accepted Paper:
Paper short abstract:
This paper explores the question of ordering kanji using artificial intelligence method, a collection of decision-based algorithms called an expert system. This research will present the expert system for ordering kanji according to chosen criteria, for purposes of linguistic analysis or education.
Paper long abstract:
Kanji can be observed in various ways: as a logographic script, as vocabulary items, or as a complex system which can be analysed and ordered. In this paper, kanji will be analysed as a collection of components, readings and statistical information of their frequency in various sources. Using that data, I will present the desicion-based algorithm for ordering kanji for various purposes based on user's input.
I purport that the human-made kanji orders such as on-reading order, grade school order, JLPT test, or simple one-source frequency orders are not optimised or useful for either educational or research purposes. A script as complex as kanji needs to take into account more than one criteria to produce an optimised order. I constructed an expert system that bases the decision an all mentioned criteria, and weighs them differently according to user's priorities.
The system is based on topological sort algorithm with customisable weights assigned to each character. The weights are affected by character frequency, components or radicals, position in grade school order and other commonly used orders, and usage in common textbooks. The frequency of a character is computed using various sources (newspaper, wikipedia, literature and Twitter) since it varies according to the source.
The user is asked to chose relevant criteria, e.g. optimisation for university level study; optimised order of JLPT N3 characters which are previously unordered; or optimised order of cross-section of two popular textbooks. In addition to that, the custom criteria can be added. The resulting order can be used for construction of teaching materials, self-study, and various kinds of linguistic analysis.
Digital humanities individual papers III
Session 1 Friday 18 August, 2023, -