• Journal of the Korea Society of Computer and Information
• /
• v.28 no.5
• /
• pp.129-153
• /
• 2023

This study was conducted in the context of the Covid-19 pandemic by analyzing a large amount of press report frames regarding the Covid-19 vaccine which is of great public interest, in order to explore the role and direction of trusted media as core elements of crisis communication. The study period lasted for eight months beginning in November 2020 when the development of the Covid-19 vaccine was in progress until June 2021. Set-up as research subjects were the Chosun Ilbo, Joongang Ilbo, Dong-A Ilbo and Hankyoreh according to their public confidence rankings and number of readers.The analysis method used structured topic Modeling (STM) and semantic network analysis. As a result, based on a clear cluster of word structures and a central analysis value, a total of 64 relevant frames, 16 for each news company, were gathered. In the third phase a comparative analysis of the four news companies was carried out to verify the organizational degree of the frames and substantial differences.

• Journal of Korean Library and Information Science Society
• /
• v.47 no.2
• /
• pp.51-70
• /
• 2016

The purpose of this study is to analyze the semantic relation network and valence-arousal dimension through the words that describe emotions in Korean language. The results of this analysis are summarized as follows. Firstly, each emotion word was semantically linked in the network. This particular feature hinders differentiating various types of "emotion words" in accordance with similarity in meaning. Instead, central emotion words playing a central role in a network was identified. Secondly, many words are classified as two categories at the valence and arousal level: (1) negative of valence and high of arousal, (2) negative of valence and middle of arousal. This aspects of Korean emotional words would be useful to analyze emotions in various text data of books and document information.

• Annual Conference on Human and Language Technology
• /
• 2012.10a
• /
• pp.99-103
• /
• 2012

의미 역 결정 (Semantic Role Labeling)은 문장 내의 술어-논항 요소들의 의미 관계를 결정하는 과정이다. 이를 위해서는 의미 표지 부착 말뭉치가 필요하지만 한국어의 경우 이 데이터가 매우 부족한 상황이다. 본 논문에서는 한국어 Proposition Bank(이하 PropBank) 말뭉치와 세종 용언 격틀 말뭉치 구축을 위한 의미 표지 부착 작업에 대해 설명한다. 표지 부착 작업은 말뭉치의 의존 관계를 사람이 파악하여 적절한 의미 역 태그를 다는 과정이고, 이 과정으로부터 얻은 말뭉치는 의미 역 결정을 위한 기계 학습 방법론의 훈련 자료로 이용된다. 이 과정에서 필요한 구문 표지 부착 밀뭉치로는 한국전자통신연구원의 구문표지 부착 말뭉치를, 그리고 언어자원으로는 한국어 PropBank의 frame file과 세종 용언 격틀 사전을 사용한다.

• Asia pacific journal of information systems
• /
• v.26 no.4
• /
• pp.577-592
• /
• 2016

The proliferation of mobile applications and the unique characteristics of the mobile environment have attracted significant research interest in understanding customers' purchasing behaviors in mobile commerce. In this study, we extend customer value theory by combining the predictors of product performance with customer value framework to investigate how in-store information creates value for customers and influences mobile application downloads. Using a data set collected from the Google Application Store, we find that customers value both text and non-text information when they make downloading decisions. We apply latent semantic analysis techniques to analyze customer reviews and product descriptions in the mobile application store and determine the embedded valuable information. Results show that, for mobile applications, price, number of raters, and helpful information in customer reviews and product descriptions significantly affect the number of downloads. Conversely, average rating does not work in the mobile environment. This study contributes to the literature by revealing the role of in-store information in mobile application downloads and by providing application developers with useful guidance about increasing application downloads by improving in-store information management.

• Journal of Information Technology and Architecture
• /
• v.10 no.1
• /
• pp.71-77
• /
• 2013

XML schema matching is the task of finding semantic correspondences between elements of two schemas. XML schema matching plays an important role in many application, such as schema integration, data integration, data warehousing, data transformation, peer-to-peer data management, semantic web etc. In this paper, we propose an XML element matching algorithm based on rules and structural properties. The proposed algorithm involves classifying elements as unique or non-unique elements according to the structural properties of XML documents and deciding on element matching in accordance with rules. We present experimental results that demonstrate the effectiveness of the proposed approach.

• Journal of Information Science Theory and Practice
• /
• v.8 no.4
• /
• pp.67-86
• /
• 2020

Information need has been one of the main motivations for a person using a search engine. Queries can represent very different information needs. Ironically, a query can be a poor representation of the information need because the user can find it difficult to express the information need. Query Expansion (QE) is being popularly used to address this limitation. While QE can be considered as a language-independent technique, recent findings have shown that in certain cases, language plays an important role. Arabic is a language with a particularly large vocabulary rich in words with synonymous shades of meaning and has high morphological complexity. This paper, therefore, provides a review on QE for Arabic information retrieval, the intention being to identify the recent state-of-the-art of this burgeoning area. In this review, we primarily discuss statistical QE approaches that include document analysis, search, browse log analyses, and web knowledge analyses, in addition to the semantic QE approaches, which use semantic knowledge structures to extract meaningful word relationships. Finally, our conclusion is that QE regarding the Arabic language is subjected to additional investigation and research due to the intricate nature of this language.

• Journal of Drive and Control
• /
• v.19 no.4
• /
• pp.104-109
• /
• 2022

For autonomous driving research using AI, datasets collected from road environments play an important role. In other countries, various datasets such as CityScapes, A2D2, and BDD have already been released, but datasets suitable for the domestic road environment still need to be provided. This paper analyzed and verified the dataset reflecting the Korean driving environment. In order to verify the training dataset, the class imbalance was confirmed by comparing the number of pixels and instances of the dataset. A similar A2D2 dataset was trained with the same deep learning model, ConvNeXt, to compare and verify the constructed dataset. IoU was compared for the same class between two datasets with ConvNeXt and mIoU was compared. In this paper, it was confirmed that the collected dataset reflecting the driving environment of Korea is suitable for learning.

• International Journal of Knowledge Content Development & Technology
• /
• v.12 no.4
• /
• pp.41-65
• /
• 2022

This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.12
• /
• pp.3364-3382
• /
• 2023

Remote sensing image segmentation plays an important role in realizing intelligent city construction. The current mainstream segmentation networks effectively improve the segmentation effect of remote sensing images by deeply mining the rich texture and semantic features of images. But there are still some problems such as rough results of small target region segmentation and poor edge contour segmentation. To overcome these three challenges, we propose an improved semantic segmentation model, referred to as MRU-Net, which adopts the U-Net architecture as its backbone. Firstly, the convolutional layer is replaced by BasicBlock structure in U-Net network to extract features, then the activation function is replaced to reduce the computational load of model in the network. Secondly, a hybrid multi-scale recognition module is added in the encoder to improve the accuracy of image segmentation of small targets and edge parts. Finally, test on Massachusetts Buildings Dataset and WHU Dataset the experimental results show that compared with the original network the ACC, mIoU and F1 value are improved, and the imposed network shows good robustness and portability in different datasets.

• Women's Health Nursing
• /
• v.24 no.3
• /
• pp.322-332
• /
• 2018

Purpose: To investigate the effect of a maternal role adjustment program on first-time mothers. Methods: The research was quasi-experimental with a non-equivalent control group non-synchronized design. Participants were first-time mothers admitted to two postpartum clinics at women's hospitals. The experimental group had 38 mothers and the control group had 35 mothers. A maternal role adjustment program was applied individually to the experimental group between the 1st and 2nd weeks after childbirth. Assessing Adaptation to Motherhood, Semantic Differential Scale-Myself as Mother, and Edinburgh Postnatal Depression Scale were used to measure effects of the program. A pre-test was conducted in the 1st week after childbirth while post-tests were conducted in the 4th and 6th weeks. Data were analyzed with $x^2$ test, Fisher's exact test, t-test, and repeated measures ANOVA using SPSS 24.0. Results: Maternal role adjustment (F=6.17, p=.015) and maternal identity (F=6.63, p=.012) were significantly increased in the experimental group compared to those in the control group. However, the difference in postpartum depression (F=1.11, p=.335) was not statistically significant between the two groups. Conclusions: The maternal role adjustment program can be utilized as an effective nursing intervention program to enhance maternal role adjustment and maternal identity for first-time mothers.