• Title, Summary, Keyword: Corpus Linguistics

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A Cognitive Study on Jeong in Korean and Amae in Japanese (한국의 '정(情)'과 일본의 '아마에(甘え)'에 대한 인지적 고찰)

  • Kim, Myung-Hee
    • Cross-Cultural Studies
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    • v.27
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    • pp.471-496
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    • 2012
  • Since Takeo Toi's discussion in The Anatomy of Dependence (1973), the concept of amae has generated considerable interest in the fields of psychology, anthropology, communication and other fields. However, there have been few agreements on the definition and functions of amae (Behrens, 2004). Furthermore, it has rarely drawn interest from linguists in general and has rarely been discussed in the context of social interaction. This study aims to examine the concept of amae in Japanese and the corresponding phenomena in Korean, and attempts to explore the similarities and differences between them. The prototype of the amae relationship is the mother-infant relationship (Doi,1973). Even an adult can assume the role of a baby, showing his or her need for dependence on others and expecting to be accepted. It turns out that amae-like phenomena frequently occur in everyday life in Korea as well (Lee, 1982). There is no single term for the concept, but it can be translated in many different ways in Korean, for example, aykyo, ayang, ungsek, erikwang, etc. It can have either positive or negative connotations depending on the situation. It seems that the psychological system that causes dependent behaviors such as ungsek in Korea is cheong, one of the key terms characterizing the Korean culture. Cheong, like amae, starts in the mother-infant relationship extending to familial and to other relationships. A corpus-based analysis shows that cheong is conceptualized as gluing people together, growing over time, and also potentially fatal because it assumes illogical, uncalculated, and personal relationships. In conclusion, unlike some Japanese scholars' claim that amae is the Japanese concept that exists only in Japan, it seems that similar phenomena do exist in Korea as well, but that Korean has no single term corresponding to amae in Japanese. It seems that cheong can be posited in Korean as the inner emotional system that makes amae-like behaviors possible, and that there is not single term, but many, designating the behaviors, possibly because the behaviors have a negative connotation and are not encouraged in Korean society.

An Exploratory Study of Collective E-Petitions Estimation Methodology Using Anomaly Detection: Focusing on the Voice of Citizens of Changwon City (이상탐지 활용 전자집단민원 추정 방법론에 관한 탐색적 연구: 창원시 시민의 소리 사례를 중심으로)

  • Jeong, Ha-Yeong
    • Informatization Policy
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    • v.26 no.4
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    • pp.85-106
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    • 2019
  • Recently, there have been increasing cases of collective petitions filed in the electronic petitions system. However, there is no efficient management system, raising concerns on side effects such as increased administrative workload and mass production of social conflicts. Aimed at suggesting a methodology for estimating electronic collective petitions using anomaly detection and corpus linguistics-based content analysis, this study conducted the followings: i) a theoretical review of the concept of collective petitions, ii) estimation of electronic collective petitions using anomaly detection based on nonparametric unsupervised learning, iii) a content similarity analysis on petitions using n-gram cosine angle distance, and iv) a case study on the Voice of Citizens of Changwon City, through which the utility of the proposed methodology, policy implications and future tasks were reviewed.

The Stream of Uncertainty in Scientific Knowledge using Topic Modeling (토픽 모델링 기반 과학적 지식의 불확실성의 흐름에 관한 연구)

  • Heo, Go Eun
    • Journal of the Korean Society for information Management
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    • v.36 no.1
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    • pp.191-213
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    • 2019
  • The process of obtaining scientific knowledge is conducted through research. Researchers deal with the uncertainty of science and establish certainty of scientific knowledge. In other words, in order to obtain scientific knowledge, uncertainty is an essential step that must be performed. The existing studies were predominantly performed through a hedging study of linguistic approaches and constructed corpus with uncertainty word manually in computational linguistics. They have only been able to identify characteristics of uncertainty in a particular research field based on the simple frequency. Therefore, in this study, we examine pattern of scientific knowledge based on uncertainty word according to the passage of time in biomedical literature where biomedical claims in sentences play an important role. For this purpose, biomedical propositions are analyzed based on semantic predications provided by UMLS and DMR topic modeling which is useful method to identify patterns in disciplines is applied to understand the trend of entity based topic with uncertainty. As time goes by, the development of research has been confirmed that uncertainty in scientific knowledge is moving toward a decreasing pattern.

A Contrastive Study on '됐어' and 'X了': Focusing on the Functions as a Discourse Marker (한국어 '됐어'와 중국어 'X了(료)'의 대조 연구 -담화표지로서의 기능을 중심으로-)

  • Zhang, Ya Nan
    • Journal of Korean language education
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    • v.28 no.4
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    • pp.181-219
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    • 2017
  • The purpose of this study is to review the functions of {됐어} and {X了} as a discourse marker on different levels, and to examine their similarities and differences. {됐어} has not been widely recognized as a discourse marker in the field of Korean linguistics and Korean language education. Therefore, in order to establish the identity of {됐어} as a discourse marker, the reasons that {됐어} can be regarded as discourse marker were explained prior to the contrastive analysis. As to the method of contrastive analysis for {됐어} and {X了}, they were analyzed on three main dimensions: that is, the textual dimension, the interpersonal dimension, and the metalinguistic dimension in the corpus consisting of scripts of Korean and Chinese sitcoms. The results are as follows. In the textual domain, {됐어} and {X了} have the function of closing the topic in common, while {X了} can indicate a new topic and transmit a topic. In terms of functions in the interpersonal domain, {됐어} and {X了} are commonly used to refuse a partner's proposal or request and to interrupt a partner's speech or action. Furthermore, in the interactional aspect, {됐어} and {X了} performs the function of expressing a response to a preceding utterance and taking the turn of speaking. The difference between them in the interpersonal domain is that {X了} performs the function of correcting a speaker's utterance. In the metalinguistic domain, {됐어} and {X了} are common in that they perform the function of expressing the dissatisfaction of the speaker, showing generosity and making a compromise with the addressee. {X了}'s distinguishing characteristics in this domain is that it can express the attitude of consoling the hearer.

Semantic Similarity Measures Between Words within a Document using WordNet (워드넷을 이용한 문서내에서 단어 사이의 의미적 유사도 측정)

  • Kang, SeokHoon;Park, JongMin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.11
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    • pp.7718-7728
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    • 2015
  • Semantic similarity between words can be applied in many fields including computational linguistics, artificial intelligence, and information retrieval. In this paper, we present weighted method for measuring a semantic similarity between words in a document. This method uses edge distance and depth of WordNet. The method calculates a semantic similarity between words on the basis of document information. Document information uses word term frequencies(TF) and word concept frequencies(CF). Each word weight value is calculated by TF and CF in the document. The method includes the edge distance between words, the depth of subsumer, and the word weight in the document. We compared out scheme with the other method by experiments. As the result, the proposed method outperforms other similarity measures. In the document, the word weight value is calculated by the proposed method. Other methods which based simple shortest distance or depth had difficult to represent the information or merge informations. This paper considered shortest distance, depth and information of words in the document, and also improved the performance.

Word Sense Similarity Clustering Based on Vector Space Model and HAL (벡터 공간 모델과 HAL에 기초한 단어 의미 유사성 군집)

  • Kim, Dong-Sung
    • Korean Journal of Cognitive Science
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    • v.23 no.3
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    • pp.295-322
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    • 2012
  • In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

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The Need for Paradigm Shift in Semantic Similarity and Semantic Relatedness : From Cognitive Semantics Perspective (의미간의 유사도 연구의 패러다임 변화의 필요성-인지 의미론적 관점에서의 고찰)

  • Choi, Youngseok;Park, Jinsoo
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.111-123
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    • 2013
  • Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.