Jinji Li

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Chinese and Korean belong to different language families in terms of word-order and morphological typology. Chinese is an SVO and morphologically poor language while Korean is an SOV and morphologically rich one. In Chinese-to-Korean SMT systems, systematic differences between the verbal systems of the two languages make the generation of Korean verbal(More)
This paper describes an approach to utilizing term weights for sentiment analysis tasks and shows how various term weight-ing schemes improve the performance of sentiment analysis systems. Previously, sentiment analysis was mostly studied under data-driven and lexicon-based frameworks. Such work generally exploits tex-tual features for fact-based analysis(More)
Subjectivity analysis is a rapidly growing field of study. Along with its applications to various NLP tasks, much work have put efforts into multilingual subjectivity learning from existing resources. Multilingual subjectivity analysis requires language-independent criteria for comparable outcomes across languages. This paper proposes to measure the(More)
To generate a proper Korean predicate, a natural modal expression is the most important factor for a machine translation (MT) system. Tense, aspect, mood, negation, and voice are the major constituents related to modal expression. The linguistic encoding of a modal expression is quite different between Chinese and Korean in terms of linguistic typology and(More)
We propose a new prototype Chinese-to-Korean machine translation system called TOTAL-CK, a prototype transfer based MT system designed for the large-scale practical domain. TOTAL-CK consists of the components of analysis, transfer, and generation. In this paper, we mainly discuss the transfer issues resulting from stylistic structural differences between(More)
ion In Chinese language processing, the recognition and analysis for serial verb constructions (SVCs) is a fascinating research topic. Chinese language researchers each may have a different definition and interpretation of SVC since the structure of SVC makes Chinese unique to other languages and contains complex semantic and pragmatic information. This(More)
This paper describes the POSTECH statistical machine translation (SMT) systems for the NTCIR-7 patent translation task. We entered two patent translation subtasks: Japanese-to-English (KLE-je), and English-to-Japanese translation (KLE-ej). The baseline systems are derived from a common phrase-based SMT framework. In addition, for Japanese-to-English(More)