• 한국정보통신학회논문지
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• 제26권11호
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• pp.1751-1754
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• 2022

The news articles collected with keyword "non face-to-face" were analyzed through topic modeling applied with LDA algorithm. In this study, collected articles were divided into two periods, period 1(the beginning of COVID-19 spread) and period 2(the end of COVID-19 spread), according to issued date of the articles. The articles of period 1 showed support for non-face-to-face treatment, smart library, the beginning of the online financial era, non-face-to-face entrance exam and employment, stock investment for main topic words. And the articles of period 2 showed conversion to non face-to-face classes, increasing unmanned stores, online finance, education industry, home treatment for main topic words. Also, further issues were discussed through visualization of topic words. These results provide evidence that education and unmanned business in non-face-to-face industries are growing.

• 한국컴퓨터정보학회논문지
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• 제13권7호
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• pp.59-66
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• 2008

본 논문에서는 인스턴트 메시징(Instant Messaging), 채팅과 같은 텍스트 기반의 대화에서 현재 발화를 기준으로 대화의 주제를 파악하고, 대화 주제 전환 여부를 판단하는 기법에 대해 기술한다. 대화는 다른 종류의 글과 다르게 길이가 매우 짧아 적은 수의 단어를 사용하고, 두 사람 이상이 참여를 하며, 대화의 이력(History)이 현재의 발화에 영향을 미친다. 이러한 특성에 따라 본 논문에서는 사용자 발화 뿐 아니라 대화 상대자의 발화에서 추출한 키워드 기반으로 주제 탐지를 하며, 대화의 이력도 고려하여 대화 주제 탐지의 정확도를 높힌 연구 결과를 기술한다. 대화주제 전환 탐지는 이전 발화와 현재 발화에서 탐지된 주제의 유사성을 계산하여, 유사성이 낮은 경우에 전환 탐지가 이루어졌다고 판단하였다. 본 논문의 실험에서 대화 주제 탐지는 88.20%. 대화 주제 전환 탐지는 87.36%의 정확도를 얻었다.

• 한국언어정보학회지:언어와정보
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• 제9권2호
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• pp.85-105
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• 2005

This study aims at investigating the 'verb-second' phenomena indicated in complex sentences of medieval Spanish. Especially, when the complex sentence is composed of a preposed adverbial clause and its succeeding main clause, the subject inversion is noticeable in the latter. The fundamental motive of this type of inversion is due to the 'verb-second' structure, in which a topic appears in the first position and the verb immediately after the topic. So it can be said that the subject inversion is a prerequisite for a verb to be located in the second position when the adverbial clause functions as a topic to the main clause, as is often the case with Germanic languages like German, Dutch, etc.. On the contrary, modern Spanish complex sentences do not show this phenomenon, with a strong tendency to locate a grammatical subject in the preverbal position. Therefore, medieval Spanish might be typologically closer to Germanic languages than to modern Spanish. In order to argue for this assumption, the formal and functional criteria by which the preposed adverbial clause could be defined as a topic NP will be examined across the comparition with left-dislocation structure.

• Nuclear Engineering and Technology
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• 제44권8호
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• pp.855-870
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• 2012

The paper deals with three main topics: a) the definition of System Thermal-Hydraulics (SYS TH), b) a historical outline for SYS TH and, c) the description of elements for reflection when planning research projects or improvement activities, this last topic being the main reason for the paper. Distinctions between basic thermal-hydraulics and computational Fluid-Dynamics (CFD) on the one side and SYS TH on the other side are considered under the first topic; stakeholders in the technology are identified. The proposal of Interim Acceptance Criteria for Emergency Core Cooling Systems in 1971 by US NRC (AEC at the time) is recognized as the starting date or the triggering event for SYS TH (second topic). The complex codes and the main experimental programs (list provided in the paper) constitute the pillars for SYS TH. Caution or warning statements are introduced in advance when discussing the third topic: a single person (or a researcher) has little to no possibility, or capability, of streamlining the forthcoming investments or to propose a roadmap for future activities. Nevertheless, the ambitious attempt to foresee developments in this area has been pursued without constraints connected with the availability of funds and with industrial benefits or interests. Demonstrating the acceptability of current SYS TH limitations and training in the application of those codes are mentioned as the main challenges for forthcoming research activities.

• 한국정보시스템학회지:정보시스템연구
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• 제30권1호
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• pp.45-64
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• 2021

Purpose The traditional topic modeling technique makes it difficult to distinguish the semantic of topics because the key words assigned to each topic would be also assigned to other topics. This problem could become severe when the number of online reviews are small. In this paper, the extended model of topic modeling technique that can be used for analyzing a small amount of online reviews is proposed. Design/methodology/approach The extended model of being proposed in this paper is a form that combines the traditional topic modeling technique and the Word2Vec technique. The extended model only allocates main words to the extracted topics, but also generates discriminatory words between topics. In particular, Word2vec technique is applied in the process of extracting related words semantically for each discriminatory word. In the extended model, main words and discriminatory words with similar words semantically are used in the process of semantic classification and naming of extracted topics, so that the semantic classification and naming of topics can be more clearly performed. For case study, online reviews related with Udo in Tripadvisor web site were analyzed by applying the traditional topic modeling and the proposed extension model. In the process of semantic classification and naming of the extracted topics, the traditional topic modeling technique and the extended model were compared. Findings Since the extended model is a concept that utilizes additional information in the existing topic modeling information, it can be confirmed that it is more effective than the existing topic modeling in semantic division between topics and the process of assigning topic names.

• 말소리와 음성과학
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• 제1권2호
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• pp.119-128
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• 2009

Many researchers have argued about the relationship between information structure and intonation. Their results can be summarized in three main points: the intonation of topic and focus in English information structures is implemented as i) a pitch accent, ii) a tune (a pitch accent + (an) edge tone(s)), or iii) a boundary tone. The purpose of this paper is to study various intonational patterns of topic and focus in English information structures, using natural conversations. In this paper, the types of topics and foci are divided, based on contrastiveness. The topics are classified as five non-contrastive and four contrastive topics. The foci are classified as neutral focus, informational focus, and contrastive focus. The results show that the intonation of the topic in English information structures is mainly implemented as a pitch accent, except for the type of the pronoun topic (Lp) which is not implemented as a pitch accent or a tune. However, the intonation of the focus is implemented as a tune in the neutral focus (Fn) and as a pitch accent or a tune in the informational focus (Fi) and the contrastive focus (Fe). In our discussion and conclusion, we suggest that it is not always true that for the meaning of contrast, the topic or the focus is represented as a $L+H^{\ast}$ pitch accent, which has been the main contrastive intonation from earlier studies.

• 정보관리학회지
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• 제32권3호
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• pp.397-412
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• 2015

본 연구에서는 커뮤니티 기반 질의응답 서비스에서의 질의할당을 위하여, 해당 커뮤니티에 축적된 질의응답 데이터 세트를 이용하여 해당 카테고리내의 토픽을 분석하고 이를 바탕으로 해당 토픽에 관심을 가지는 이용자의 관심 토픽을 분석하고자 하였다. 특정 카테고리 내의 토픽을 분석하기 위해서 LDA기법을 사용하였고 이를 이용하여 이용자의 관심 토픽을 모델링하였다. 나아가, 커뮤니티에 새롭게 유입되는 질의에 대한 토픽을 분석한 후, 이를 바탕으로 해당 토픽에 대해 관심을 가지고 있는 이용자를 추천하기 위한 일련의 방법들을 실험하였다.

• Journal of Information Science Theory and Practice
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• 제6권4호
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• pp.39-53
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• 2018

While the body of research on metadata has grown substantially, there has been a lack of systematic analysis of the field of metadata. In this study, we attempt to fill this gap by examining metadata literature spanning the past 20 years. With the combination of a text mining technique, topic modeling, and network analysis, we analyzed 2,713 scholarly papers on metadata published between 1995 and 2014 and identified main topics and trends in metadata research. As the result of topic modeling, 20 topics were discovered and, among those, the most prominent topics were reviewed in detail. In addition, the changes over time in the topic composition, in terms of both the relative topic proportions and the structure of topic networks, were traced to find past and emerging trends in research. The results show that a number of core themes in metadata research have been established over the past decades and the field has advanced, embracing and responding to the dynamic changes in information environments as well as new developments in the professional field.

• 한국IT서비스학회지
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• 제15권3호
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• pp.71-95
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• 2016

In recent years, text mining has been used to extract meaningful insights from the large volume of unstructured text data sets of various domains. As one of the most representative text mining applications, topic modeling has been widely used to extract main topics in the form of a set of keywords extracted from a large collection of documents. In general, topic modeling is performed according to the weighted frequency of words in a document corpus. However, general topic modeling cannot discover the relation between documents if the documents share only a few terms, although the documents are in fact strongly related from a particular perspective. For instance, a document about "sexual offense" and another document about "silver industry for aged persons" might not be classified into the same topic because they may not share many key terms. However, these two documents can be strongly related from the R&D perspective because some technologies, such as "RF Tag," "CCTV," and "Heart Rate Sensor," are core components of both "sexual offense" and "silver industry." Thus, in this study, we attempted to discover the differences between the results of general topic modeling and R&D perspective topic modeling. Furthermore, we package social issues from the R&D perspective and present a prototype system, which provides a package of news articles for each R&D issue. Finally, we analyze the quality of R&D perspective topic modeling and provide the results of inter- and intra-topic analysis.

• 대한간호학회지
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• 제51권1호
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• pp.68-79
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• 2021

Purpose: This study aimed to analyze the mass and social media contents and structures related to particulate matter before and after the policy enforcement of the comprehensive countermeasures for particulate matter, derive nursing implications, and provide a basis for designing health policies. Methods: After crawling online news articles and posts on social networking sites before and after policy enforcement with particulate matter as keywords, we conducted topic and semantic network analysis using TEXTOM, R, and UCINET 6. Results: In topic analysis, behavior tips was the common main topic in both media before and after the policy enforcement. After the policy enforcement, influence on health disappeared from the main topics due to increased reports about reduction measures and government in mass media, whereas influence on health appeared as the main topic in social media. However semantic network analysis confirmed that social media had much number of nodes and links and lower centrality than mass media, leaving substantial information that was not organically connected and unstructured. Conclusion: Understanding of particulate matter policy and implications influence health, as well as gaps in the needs and use of health information, should be integrated with leadership and supports in the nurses' care of vulnerable patients and public health promotion.