• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.345-352
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• 2006

The practical English-Korean machine translation system should be able to translate long sentences quickly and accurately. The intra-sentence segmentation method has been proposed and contributed to speeding up the syntactic analysis. This paper proposes the syntactic category prediction method using decision trees for getting accurate parsing results. In parsing with segmentation, the segment is separately parsed and combined to generate the sentence structure. The syntactic category prediction would facilitate to select more accurate analysis structures after the partial parsing. Thus, we could improve the parsing accuracy by the prediction. We construct features for predicting syntactic categories from the parsed corpus of Wall Street Journal and generate decision trees. In the experiments, we show the performance comparisons with the predictions by human-built rules, trigram probability and neural networks. Also, we present how much the category prediction would contribute to improving the translation quality.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.13-23
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• 2022

In this study we leveraged a probing method to evaluate how a pre-trained L2 LSTM language model represents sentences with relative and coordinate clauses. The probing experiment employed adapted models based on the pre-trained L2 language models to trace the syntactic properties of sentence embedding vector representations. The dataset for probing was automatically generated using several templates related to different sentence structures. To classify the syntactic properties of sentences for each probing task, we measured the adaptation effects of the language models using syntactic priming. We performed linear mixed-effects model analyses to analyze the relation between adaptation effects in a complex statistical manner and reveal how the L2 language models represent syntactic features for English sentences. When the L2 language models were compared with the baseline L1 Gulordava language models, the analogous results were found for each probing task. In addition, it was confirmed that the L2 language models contain syntactic features of relative and coordinate clauses hierarchically in the sentence embedding representations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.123-131
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• 1994

This paper describes on the analysis of morphemes and it's synthesis being constituted of Korean word phrases. To analyze morphemes, we propose the introduction of "morph" for morpheme features in lexicon and the usage of chart data structures. it controls over the generation of unnecessary morpheme, and extracts every possible morpheme unit in a word phrase which minimized lexicon investigation by using heuristic information. Moreover, to synthesize morphemes, it is composed of every possible analyzed morphemes in word phrases to take advantage of speech and union information which can be obtained for program. Therefore, the systhesis of analyzed morphemes were designed to aid a syntactic analysis next step of natural language processing. This system for analyzing and systhesizing morpheme was to generate a word phrase by unifying syntactic and semantic features of analyzed morphemes in lexicon, and then established by C language of the personal computer.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.492-497
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• 2014

In this paper, we propose a method of retrieving opinioned tweets in Twitter, which is the one of the popular Social Network Services and shares diverse opinions among various users. In typical opinion retrieval systems, they may consider the presence of sentiment phrases (subjectivity) as the important factor even if the subjective phrases are not related to a given query or speaker. To alleviate these problems, we utilized the syntactic structure of a sentence to identify the relationships between 1) subjectivity-query and 2) subjectivity-speaker and 3) the syntactic role of subjectivity. Besides, our learning-to-rank approach is trained to retrieve opinioned tweets based on query-relevance, textual features, user information, and Twitter-specific features. Experimental results on real world data show that our proposed method can achieve better performance than several baseline methods in terms of precision and nDCG.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.141-144
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• 2007

The longer the input sentences, the worse the syntactic parsing results, Therefore, a long sentence is first divided into several clauses and syntactic analysis for each clause is performed. Finally, all the analysis results art merged into one, In the merging process, it is difficult to determine the dependency among clauses, To handle such syntactic ambiguity among clauses, this paper proposes an SVM-based clause-dependency determination method. We extract various features from clauses, and analyze the effect of each feature on the performance. We also compare the performance of our proposed method with those of previous methods.

• Cross-Cultural Studies
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• v.37
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• pp.309-334
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• 2014

This study is based on the Korean-Chinese parallel corpus, utilizing the Korean connective morpheme '-myenseo' and contrasting with the Chinese expression. Korean learners often struggle with the use of Korean Connective Morpheme especially when there is a lexical gap between their mother language. '-myenseo' is of the most use Korean Connective Morpheme, it usually contrast to the Chinese coordinating conjunction. But according to the corpus, the contrastive Chinese expression to '-myenseo' is more than coordinating conjunction. So through this study, can help the Chinese Korean language learners learn easier while studying '-myenseo', because the variety Chinese expression are found from the parallel corpus that related to '-myenseo'. In this study, firstly discussed the semantic features and syntactic characteristics of '-myenseo'. The significant semantic features of '-myenseo' are 'simultaneous' and 'conflict'. So in this chapter the study use examples of usage to analyse the specific usage of '-myenseo'. And then this study analyse syntactic characteristics of '-myenseo' through the subject constraint, predicate constraints, temporal constraints, mood constraints, negatives constraints. then summarize them into a table. And the most important part of this study is Chapter 4. In this chapter, it contrasted the Korean connective morpheme '-myenseo' to the Chinese expression by analysing the Korean-Chinese parallel corpus. As a result of the analysis, the frequency of the Chinese expression that contrasted to '-myenseo' is summarized into