• Journal of English Language & Literature
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• v.56 no.6
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• pp.1047-1065
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• 2010

English inversion constructions are not only hard for non-native speakers to learn but also difficult to teach mainly because of their intriguing grammatical and discourse properties. This paper addresses grammatical issues in learning or teaching the so-called 'predicate inversion (PI)' construction (e.g., Equally important in terms of forest depletion is the continuous logging of the forests). In particular, we chart the grammatical (distributional, syntactic, semantic, pragmatic) properties of the PI construction, and argue for adata-driven teaching for English grammar. To depart from the arm-chaired style of grammar teaching (relying on author-made simple sentences), our teaching method introduces a datadriven teaching. With total 25 university students in a grammar-related class, students together have analyzed the British Component of the International Corpus of English (ICE-GB), containing about one million words distributed across a variety of textual categories. We have identified total 290 PI sentences (206 from spoken and 87 from written texts). The preposed syntactic categories of the PI involve five main types: AdvP, PP, VP(ed/ing), NP, AP, and so, all of which function as the complement of the copula. In terms of discourse, we have observed, supporting Birner and Ward's (1998) observation that these preposed phrases represent more familiar information than the postposed subject. The corpus examples gave us the three possible types: The preposed element is discourse-old whereas the postposed one is discourse-new as in Putting wire mesh over a few bricks is a good idea. Both preposed and postposed elements can also be discourse new as in But a fly in the ointment is inflation. These two elements can also be discourse old as in Racing with him on the near-side is Rinus. The dominant occurrence of the PI in the spoken texts also supports the view that the balance (or scene-setting) in information structure is the main trigger for the use of the PI construction. After being exposed to the real data and in-depth syntactic as well as informationstructure analysis of the PI construction, it is proved that the class students have had a farmore clear understanding of the construction in question and have realized that grammar does not mean to live on by itself but tightly interacts with other important grammatical components such as information structure. The study directs us toward both a datadriven and interactive grammar teaching.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.71-81
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• 1997

This paper proposes noun and affix extraction methods using conjunctive information for making an automatic indexing system thorugh morphological analysis and syntactic analysis. The korean language has a peculiar spacing words rule, which is different from other languages, and the conjunctive information, which is extracted from the rule, can reduce the number of multiple parts of speech at a minimum cost. The proposed algorithms also solve the problem that one word is seperated by newline charcter. We show efficiency of the proposed algorithms through the process of morhologica analyzing.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.96-104
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• 2007

We explore a computational algebraic approach to grammar via pregroups. We examine how the structures of Japanese causatives can be treated in the framework of a pregroup grammar. In our grammar, the dictionary assigns one or more syntactic types to each word and the grammar rules are used to infer types to strings of words. We developed a practical parser representing our pregroup grammar, which validates our analysis.

• Journal of The Korea Institute of Healthcare Architecture
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• v.22 no.1
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• pp.17-28
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• 2016

Purpose: The purpose of this paper is to analyze the spatial configurations of a sample of Korean regional emergency medical centers (REMCs) to explore its underlying genotypes and thus produce a base line data for the analysis and evaluations of future REMCs designs using space syntax theory. Methods: Space syntax analysis was used as a major tool for the analysis and exploration of Genotype. The measures of Integration(overall integration with exterior and without exterior as well as the integration of individual clinical spaces for each center), base difference factor (DF) and Space link ratio were calculated for a sample of seven Korean REMCs. Results: The result shows a strikingly similar pattern of Syntactic measures across the sample, the mean integration of sample ranges from 0.82-0.99 with exterior (while considering the exterior space as a root) and 0.81-1.01 without exterior (considering the connections of interior spaces only with no outside connection). The base difference factor (DF) of the sample varies from 0.60-0.81 with exterior and from 0.59-0.82 without exterior. Case number-1 was identified as non-genotype with differing order of Syntactic values. Although the genotype had different forms, layouts and even sizes, these results cannot be explained by Phenotypical comparisons. Implications: This study will contribute to the configurational analysis and evaluation of existing and future Korean REMCs design and practice of emergency healthcare delivery system in Korea.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.576-593
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• 2021

In this study, in order to investigate the factors that affect the percentage of correct answers and the degree of discrimination of the TOEIC test, a regression analysis was performed using corpus indicators that influence correct answer rate and the degree of discrimination for each part derived from the item analysis. The basic calculation word_length, consistency index LSA_overlap_adjacent_sentences, lexical diversity MTLD_VOCD, conjunction All_logical_causal_connectives_incidence, situational model casual_particles_causal_verbs_Ratio, syntactic complexity Left_embeddedness, and syntactic pattern density Infinitive_density were found to have negative effects. These factors that lower the correct answer rate can be utilized when setting learning goals. Vocabulary diversity index MTLD_VOCD, conjunction Additive_connectives_incidence, syntactic pattern density Infinitive_density, and lexical information person1_2_pronoun_incidence were found to have a positive effect. Factors influencing the increase in discrimination may provide important information for developing a learning program.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.291-298
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• 2022

In this paper, we present a method for dependency parsing with chunking in Korean. Dependency parsing is a task of determining a governor of every word in a sentence. In general, we used to determine the syntactic governor in Korean and should transform the syntactic structure into semantic structure for further processing like semantic analysis in natural language processing. There is a notorious problem to determine whether syntactic or semantic governor. For example, the syntactic governor of the word "먹고 (eat)" in the sentence "밥을 먹고 싶다 (would like to eat)" is "싶다 (would like to)", which is an auxiliary verb and therefore can not be a semantic governor. In order to mitigate this somewhat, we propose a Korean dependency parsing after chunking, which is a process of segmenting a sentence into constituents. A constituent is a word or a group of words that function as a single unit within a dependency structure and is called a chunk in this paper. Compared to traditional dependency parsing, there are some advantage of the proposed method: (1) The number of input units in parsing can be reduced and then the parsing speed could be faster. (2) The effectiveness of parsing can be improved by considering the relation between two head words in chunks. Through experiments for Sejong dependency corpus, we have shown that the USA and LAS of the proposed method are 86.48% and 84.56%, respectively and the number of input units is reduced by about 22%p.

• Journal of the Korean Institute of Telematics and Electronics
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• v.16 no.3
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• pp.1-8
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• 1979

This is Part I of a two-part article on Korean character processing by a computer. In part I, the problems in Korean character processing are identified and the theoretical foundation is laid out as a viable solution to them. The one-and two-dimensional syntactic structures of Korean characters are formally defined by means of BNF and " Patternal structure " respectively. Formal discussion of lexical and syntactic algorithms is given for character conversion. This character conversion algorithm is applicable to both input and output. For device-independence and implementation-independence, the concept of " cardinal symbol set " is introduced. We will present a historical survey of Korean character processing and discussion of implementation problems for the above algorithm In Part II.lgorithm In Part II.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.3
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• pp.74-80
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• 2002

There are many researches on post-processing methods for the Korean continuous speech recognition enhancement using natural language processing techniques. It is very difficult to use a formal morphological analyzer for improving the speech recognition because the analysis technique of natural language processing is mainly for formal written languages. In this paper, we propose a speech recognition enhancement model using syntactic unit of morphemes. This approach uses the functional word level longest match which dose not consider spacing words. We describe the post-processing mechanism for the improving speech recognition by using proposed model which uses the relationship of phonological structure information between predicates md auxiliary predicates or bound nouns that are frequently occurred in Korean sentences.