• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.343-348
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• 2019

In recent years, extractive summarization systems based on end-to-end deep learning models have become popular. These systems do not require human-crafted features and adopt data-driven approaches. However, previous related studies have shown that linguistic analysis features such as part-of-speeches, named entities and word's frequencies are useful for extracting important sentences from a document to generate a summary. In this paper, we propose an extractive summarization system based on deep neural networks using conventional linguistic analysis features. In order to prove the usefulness of the linguistic analysis features, we compare the models with and without those features. The experimental results show that the model with the linguistic analysis features improves the Rouge-2 F1 score by 0.5 points compared to the model without those features.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.169-172
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• 2001

In recent years, many studies regarding the modeling of fuzzy system have been conducted. In this paper, a new computational approach to modeling of linguistic fuzzy system is proposed The fuzzy system is modeled as a combination of affine systems, The proposed method can be used in a rigorous stability analysis of fuzzy system including the linguistic fuzzy controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3760-3767
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• 2013

The purpose of this study is to investigate the relationship among domain-general creativity, linguistic intelligence, Korean language grade and linguistic creativity of elementary school student. And to confirm the relative predictive power of domain-general creativity variables in predicting elementary school students' linguistic creativity. The instruments used in this study were 'TTCT', 'Essay writing' and 'Linguistic intelligence ' and school grade of Korean language. Self-reported response data on these instruments from 338, 4th grade elementary school students in Seoul were analyzed. The data were analyzed with descriptive statistics, Pearson correlations, multiple stepwise regression analysis and ANOVA by using SPSS 18.0. The major results of this study were as follows; First, the correlations among domain-general creativity, Korean language grade and linguistic creativity were significant. Second, Abstractness of title were the best predictor of linguistic creativity in elementary school students.

• Journal of The Korean Association For Science Education
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• v.32 no.4
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• pp.760-774
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• 2012

The purpose of this study was to analyze the characteristic of the linguistic interaction according to leadership type of the leader in the scientific inquiry activity groups and examine how leadership factors affect the linguistic interaction within a group. In this investigation, leaders among 12 elementary school students were chosen by considering results of the leadership diagnosis that tested 3 leadership factors: vision and promotion, assignment responsibility, and decision-making. The members of the groups were organized according to scientific inquiry ability and academic achievement; the groups were assigned to perform scientific inquiry activities. The linguistic interaction was largely divided into the cognitive domain and the affective domain for analysis. According to the results, the frequency of linguistic interaction within a group sorted by leadership type is more influenced by the cognitive domain than the affective domain. The highest frequency of linguistic interaction appeared within the group that had vision and promotion type leader. Assumedly, the vision and confidence of the vision and promotion type leader produced such an outcome. While solving the assignments, linguistic interaction in all three groups had more cognitive domain than affected domain. Linguistic interaction in cognitive domain displayed only low level of linguistic interaction in relation to the experiment itself: high level of linguistic interaction barely occurred. In the case of affected domain, active participation appeared more frequently than maintaining the mood: Interactions related to restricting the group members actions to solve the assignment appeared more frequently than those for maintaining the mood.

• Annual Conference on Human and Language Technology
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• 2001.10d
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• pp.48-53
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• 2001

인터넷 환경의 급속한 성장과 더불어 기존의 텍스트 정보들이 다양한 형태의 멀티미디어 정보(소리, 이미지, 동영상 등)로 대체되었다. 이로 인해 멀티미디어 정보검색의 필요성이 대두되기 시작했다. 멀티미디어 정보검색 중 이미지검색은 크게 주석기반과 특징기반 (color, shape, texture 등) 검색으로 나눌 수 있다. 본 고는 이미지 검색 중 전처리에 해당하는 색상어 질의처리의 한 방법을 제안한다. 즉, 사용자에게 익숙한 자연어 질의로부터 이미지의 특징에 해당하는 색상 정보와 주석에 해당하는 키워드 정보를 중심어 후위원칙기반으로 파싱트리를 구성한 후, 후위순회방식에 의해 불리언 검색을 수행하는 방법을 제안한다.

• Language and Information
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• v.20 no.1
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• pp.111-125
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• 2016

In this paper I argue that the subject in a Korean kes-cleft construction denotes the discourse referent that stands for the entity that satisfies the description of the cleft clause. This denotation thereby can be understood as a meta-linguistic referent which refers to the linguistic expression for a presupposed entity. In support of this claim, it is shown an anaphoric expression kekes also can be analyzed as a meta-linguistic referent. This analysis can explain why the subject and the predicate of a kes-cleft in Korean allow animacy crash.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1187-1190
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• 1993

The problem of the optimization of fuzzy relational models for dealing with (non-fuzzy) numerical data is investigated. In this context, interfaces optimization assumes particular importance, becoming a determinant factor in what concerns the overall model performance. Considering this, several scenarios for building fuzzy relational models are presented. These are: (i) optimizing I/O interfaces in advance (independently from the linguistic part of the model); (ii) optimizing I/O interfaces in advance and allowing that their optimized parameters may change during the learning of the linguistic part of the model; (iii) build simultaneously both interfaces and the linguistic subsystem; and (iv) build simultaneously both linguistic subsystem and interfaces, now subject to semantic integrity constraints. As linguistic subsystems, both a basic type and an extended versions of fuzzy relation equations are exploited in each one of these scenarios. A comparative analysis of the differ nt approaches is summarized.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.348-356
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• 2022

The main objective of this paper is to probe the extent to which misinformation propagated through the different social media platforms contribute effectively in the process of directing, shaping and reshaping societal awareness of Saudis. In so doing, this paper attempts to delve into the relationship between linguistic misinformation and societal awareness, by exploring the perception of Saudis towards social media news, particularly misinformation and the extent to which this misinformation influences the social attitudes of Saudis in terms of various societal issues. Two main research questions are addressed in this study. First, to what extent does social media misinformation affect Saudis' awareness? Second, what are the linguistic manifestations of misinformation presented in the different social platforms? Two main findings have been recorded in this study: first, misinformation significantly contributes to the societal awareness of Saudis; and, second, however misinformation is linguistically manifested at the different levels of linguistic analysis, it is highly representative at the lexicalization level of language use.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.49-55
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• 2019

The character dialogue created by AI is unnatural when compared with human-made dialogue, and it can not reveal the character's personality properly in spite of remarkable development of AI. The purpose of this paper is to classify characters through the linguistic style and to investigate the relation of the specific linguistic style with the personality. We analyzed the dialogues of 92 characters selected from total 60 movies categorized four movie genres, such as romantic comedy, action, comedy and horror/thriller, using Linguistic Inquiry and Word Count (LIWC), a text analysis software. As a result, we confirmed that there is a unique language style according to genre. Especially, we could find that the emotional tone than analytical thinking are two important features to classify. They were analyzed as very important features for classification as the precision and recall is over 78% for romantic comedy and action. However, the precision and recall were 66% and 50% for comedy and horror/thriller. Their impact on classification was less than romantic comedy and action genre. The characters of romantic comedy deal with the affection between men and women using a very high value of emotional tone than analytical thinking. The characters of action genre who need rational judgment to perform mission have much greater analytical thinking than emotional tone. Additionally, in the case of comedy and horror/thriller, we analyzed that they have many kinds of characters and that characters often change their personalities in the story.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.