• Language and Information
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• v.5 no.1
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• pp.87-105
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• 2001

This paper categorizes currently available theories of focus into two major types a 'discourse structure approach'(DSA) and a 'sentence structure approach'(SSA) The former DSA is intended to refer to a type of approach that analyzes focus only in terms of the discourse structure in which a focused sentence occurs. The alternative semantics approach which is the most widely available theory of focus belongs to this The latter SSA is meant to refer to a type of theory that analyzes focus in terms of sentence-internal structure, This study supports the SSA be revealing some empirical problems of the DSA that arise is analyzing two different kinds of focus, the A-accented focus and the B-accented focus (contrastive topic), and provides a brief sketch of a comprehensive analysis of focus and contrastive topic.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1639-1648
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• 1988

This paper deals with an analyzing method of the Korean syntax to implement a natural language understanding system. A matrix of the syntactic structure is derived by the structural features of the Korean language. The modificatoty and conceptual structures are extracted from the matrix and the predicate logic form is expressed by extracting the phrase, clause and conceptual structure in the analyzing process. This logic form constructs an knowledge base of the sentence and proposes the possibility of the inference.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.101-121
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• 2018

This study proposes the analysis method in sentence semantics that can be automatically identified and processed as appropriate items in the system according to the composition of the sentences contained in the data corresponding to the logical semantic structure metadata of the research papers. In order to achieve the purpose, the structure of sentences corresponding to 'Research Objectives' and 'Research Outcomes' among the semantic structure metadata was analyzed based on the number of words, the link word types, the role of many-appeared words in sentences, and the end types of a word. As a result of this study, the number of words in the sentences was 38 in 'Research Objectives' and 212 in 'Research Outcomes'. The link word types in 'Research Objectives' were occurred in the order such as Causality, Sequence, Equivalence, In-other-word/Summary relation, and the link word types in 'Research Outcomes' were appeared in the order such as Causality, Equivalence, Sequence, In-other-word/Summary relation. Analysis target words like '역할(Role)', '요인(Factor)' and '관계(Relation)' played a similar role in both purpose and result part, but the role of '연구(Study)' was little different. Finally, the verb endings in sentences were appeared many times such as '~고자', '~였다' in 'Research Objectives', and '~었다', '~있다', '~였다' in 'Research Outcomes'. This study is significant as a fundamental research that can be utilized to automatically identify and input the metadata element reflecting the common logical semantics of research papers in order to support researchers' scholarly sensemaking.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.90-93
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• 2008

In natural language, it is common that repetitive constituents in an expression are to be left out and it is necessary to figure out the constituents omitted at analyzing the meaning of the sentence. This paper is on recognition of boundaries of parallel noun phrases by figuring out constituents omitted. Recognition of parallel noun phrases can greatly reduce complexity at the phase of sentence parsing. Moreover, in natural language information retrieval, recognition of noun with modifiers can play an important role in making indexes. We propose an unsupervised probabilistic model that identifies parallel cores as well as boundaries of parallel noun phrases conjoined by a conjunctive particle. It is based on the idea of swapping constituents, utilizing symmetry (two or more identical constituents are repeated) and reversibility (the order of constituents is changeable) in parallel structure. Semantic features of the modifiers around parallel noun phrase, are also used the probabilistic swapping model. The model is language-independent and in this paper presented on parallel noun phrases in Korean language. Experiment shows that our probabilistic model outperforms symmetry-based model and supervised machine learning based approaches.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.58-64
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• 2018

The Extraposition phenomenon in English has been analyzed mainly through two approaches: a derivational approach under the Principles & Parameters framework (P&P) and a representational approach under the early Minimalist framework (MP). The first one tries to understand the phenomenon as a result of the movement of a Big Subject first to the end of a sentence which is then followed by the insertion of an expletive 'it' to the empty Subject position. On the other hand, the second one tries to understand it by way of assuming a Big Subject originally base-generated at the end of a sentence which is followed by the insertion of an expletive 'it' to the empty Subject position. The two approaches, however, are not free from theoretical defects at all: the full derivational approach was under controversy in terms of (1) the failure of the Binding Theory and (2) its inability to suggest anything about the marginal reading issue. On the while, the representational approach has been argued (1) to violate the thematic hierarchy that should be kept in D-structure, and (2) to be also unable to suggest the slightest difference in marginal reading issue as the first one. In this paper I focus mainly on analyzing the 'It'-Extraposition phenomenon in the Optimality Theory. I will show that by way of (i) some newly developed constraints such as Subj., and AHSubj. and (ii) a constraint hierarchy of Subj.>>AHSubj., the controversies of 'It-Extraposition' such as (1) the analysis of construction and (2) the very closely related issue of 'marginal reading issue' can be explained properly.

• Journal of Educational Research in Mathematics
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• v.26 no.4
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• pp.635-662
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• 2016

Combinatorics, the basis of probabilistic thinking, is an important area of mathematics and closely linked with other subjects such as informatics and STEAM areas. But combinatorics is one of the most difficult units in school mathematics for leaning and teaching. This study, using the designed combinatorial models and executable expression, aims to analyzes the eye movement of graduate students when they translate the written combinatorial problems to the corresponding executable expression, and examines not only the understanding process of the written combinatorial sentences but also the degree of difficulties depending on the combinatorial semantic structures. The result of the study shows that there are two types of solving process the participants take when they solve the problems : one is to choose the right executable expression by comparing the sentence and the executable expression frequently. The other approach is to find the corresponding executable expression after they derive the suitable mental model by translating the combinatorial sentence. We found the cognitive processing patterns of the participants how they pay attention to words and numbers related to the essential informations hidden in the sentence. Also we found that the student's eyes rest upon the essential combinatorial sentences and executable expressions longer and they perform the complicated cognitive handling process such as comparing the written sentence with executable expressions when they try the problems whose meaning structure is rarely used in the school mathematics. The data of eye movement provide meaningful information for analyzing the cognitive process related to the solving process of the participants.

• Phonetics and Speech Sciences
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• v.5 no.1
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• pp.81-90
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• 2013

During adolescence the mutational period is characterized by the changes in the laryngeal structure, the length of the vocal cords, and a tone of voice. Usually, adolescents at 15 or 16 reach the voice of adults but the mutational period is sometimes delayed. Therefore, studies on the voice of adolescents between 16 ~ 18 right after the mutational period are required. Accordingly, this paper attempted to provide basic data about the normal standard for patients with voice disorders during this period by evaluating the vocal characteristics of males and females between 16 ~ 18 with an objective device bycomparing and analyzing them by sex and age. The study was conducted on a total of 60 subjects composed of each 10 subjects of each age. The vocal analysis was conducted by MPT (Maximum Phonation Time) measurement, sustained vowels and sentence reading. As for /a/ sustained vowels, fundamental frequency, hereinafter referred to as $F_0$, jitter, shimmer, noise-to-harmonic ratio, hereinafter referred to as NHR were measured by using the Multi-dimensional voice program (MDVP) among the Multi-Speech program of Computerized Speech Lab (Kay Elemetrics). The sentence reading, mean $F_0$, maximum $F_0$ and minimum $F_0$ were measured using the Real-Time Pitch (RTP) Model 5121 among the Multi-Speech program of Computerized Speech Lab (Kay Elemetrics). As a result, according to sex, there were statistically significant differences in $F_0$, jitter, shimmer, mean $F_0$, maximum $F_0$, and minimum $F_0$; and according to age, there were statistically significant differences in MPT. In conclusion, the voice of the adolescents between 16 ~ 18 reached the maturity levels of adults but the voice quality which can be considered on the scale of voice disorders showed transition to the voice of an adult during the mutational period.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.199-204
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• 2022

This study was carried out in an L2 writing class using machine translation. The aim of this study was to explore what types of errors are identified the most frequently in the Korean-to-English machine translation output and what causes those errors. The participants were seven EFL university students who completed three writing tasks throughout the semester. The findings of data analysis indicated that the most common errors were seen in sentence structure and mechanics, and those errors in the translated texts were caused by the errors in the Korean source texts.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.219-234
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• 2018

In this study, we explored the possibility of automating the process of analyzing elements of scientific argument in the context of a Korean classroom. To gather training data, we collected 990 sentences from science education journals that illustrate the results of coding elements of argumentation according to Toulmin's argumentation structure framework. We extracted 483 sentences as a test data set from the transcription of students' discourse in scientific argumentation activities. The words and morphemes of each argument were analyzed using the Python 'KoNLPy' package and the 'Kkma' module for Korean Natural Language Processing. After constructing the 'argument-morpheme:class' matrix for 1,473 sentences, five machine learning techniques were applied to generate predictive models relating each sentences to the element of argument with which it corresponded. The accuracy of the predictive models was investigated by comparing them with the results of pre-coding by researchers and confirming the degree of agreement. The predictive model generated by the k-nearest neighbor algorithm (KNN) demonstrated the highest degree of agreement [54.04% (${\kappa}=0.22$)] when machine learning was performed with the consideration of morpheme of each sentence. The predictive model generated by the KNN exhibited higher agreement [55.07% (${\kappa}=0.24$)] when the coding results of the previous sentence were added to the prediction process. In addition, the results indicated importance of considering context of discourse by reflecting the codes of previous sentences to the analysis. The results have significance in that, it showed the possibility of automating the analysis of students' argumentation activities in Korean language by applying machine learning.

• Journal of Korean Library and Information Science Society
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• v.51 no.3
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• pp.53-80
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• 2020

Library Week was established in 1964 and has continued without interruption for 56 years. It has grown to become one of the largest and most important activities within the library field today. The Korean Library Association publicly selects slogans to be used for Library Week publicity purposes and their poster advertising campaign. A study and evaluation analyzing slogan contents was performed to determine the overall effects of these slogans on the public and provide suggestions for more effective and focused slogans as part of a branding strategy. To achieve this purpose, the contents of 116 official slogans of the library week were analyzed according to the linguistic techniques and key words suggested by Young-Jun Park (2001). As a result, there were 103 slogans (88.79%) composed of only 'Korean characters'. And the key scoring type with the highest number of hits was the word 'sentences' 46 units (39.66%). Furthermore the word in the slogans resulting in the highest number of hits was 'library' with 111 units (96.52%). Therefore, it can be said that most of the weekly slogans of the library are 'sentence type' consisting of 'Korean characters' containing the word 'library'.