Fó (佛), Pwuche (仏体), and Hotoke (保止氣)

The aim of this article is to discuss how the Chinese loanword fó (佛) was incorporated into pre-Old Korean (pre-OK), Old Korean (OK), and Western Old Japanese (WOJ) on the basis of textual research using various primary sources from China, Korea, and Japan. The author proposes that two routes exist to explain the borrowing of the Chinese word fó (佛) into pre-OK, OK, and WOJ: one route from the Six Dynasties to the Korean Three Kingdoms period to Japan's pre-Nara period, and one from the Sui and Tang dynasties to the Unified Silla and Koryŏ periods.

A Chinese Word by Jacques Derrida

Some scholars claim that in Derrida's Of Grammatology the author presents China and its script as essentially and radically Other when compared to the West. In this paper, I argue that Derrida's discussion of Leibniz, his critique of the notions of ‘phonetic writing’ and ‘ideograph’, and the distinction he makes between ‘logocentrism’ and ‘phonocentrism’, enables him to deconstruct an essentialist conception of China or Chinese writing. However, far from conceiving China in a relativist or ethnocentric manner, Derrida also pays attention to the historicity of the encounter between European philosophy and China. In order to underline the transcultural potential of deconstruction, I discuss the concept of ‘crypt’ in light of the Chinese translation of the word ‘ différance’. This allows me to reinterpret what I claim to be Derrida's problematic reference to Chinese writing as ‘outside of all logocentrism’ from the point of view of his philosophy of translation. 1

The Xu-Based Approach to Second Language Learning

This special issue provides an overview of the xu-argument, a newly emerging view on language acquisition. The view is new in that it makes two key points: i) language is acquired through xu, a Chinese word with a composite meaning of completion, extension and creation (CEC) (Wang, 2016), and ii) high efficiency in learning a language is achieved by xu. Using a single word to capture the highly complex human endowment of language learning might be too ambitious an attempt. Convincing justifications and supporting evidence are needed to verify this claim, as the papers in this issue are intended to do.

Modeling multi-prototype Chinese word representation learning for word similarity

The word similarity task is used to calculate the similarity of any pair of words, and is a basic technology of natural language processing (NLP). The existing method is based on word embedding, which fails to capture polysemy and is greatly influenced by the quality of the corpus. In this paper, we propose a multi-prototype Chinese word representation model (MP-CWR) for word similarity based on synonym knowledge base, including knowledge representation module and word similarity module. For the first module, we propose a dual attention to combine semantic information for jointly learning word knowledge representation. The MP-CWR model utilizes the synonyms as prior knowledge to supplement the relationship between words, which is helpful to solve the challenge of semantic expression due to insufficient data. As for the word similarity module, we propose a multi-prototype representation for each word. Then we calculate and fuse the conceptual similarity of two words to obtain the final result. Finally, we verify the effectiveness of our model on three public data sets with other baseline models. In addition, the experiments also prove the stability and scalability of our MP-CWR model under different corpora.