• Communications of the Korean Institute of Information Scientists and Engineers
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• v.33 no.4
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• pp.30-38
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• 2015

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.30 no.11
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• pp.68-77
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• 2012

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.32 no.3
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• pp.61-70
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• 2014

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.9-21
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• 2021

The study aims to identify convergence and trends in technology-based patent data for the biohealth sector in IP5 countries (KR, EP, JP, US, CN) and present the direction of development in that industry. We used patent co-classification analysis-based network analysis and TF-IDF-based text mining as the principal methodology to understand the current state of technology convergence. As a result, the technology convergence cluster in the biohealth industry was derived in three forms: (A) Medical device for treatment, (B) Medical data processing, and (C) Medical device for biometrics. Besides, as a result of trend analysis based on technology convergence results, it is analyzed that Korea is likely to dominate the market with patents with high commercial value in the future as it is derived as a market leader in (B) medical data processing. In particular, the field is expected to require technology convergence activation policies and R&D support strategies for the technology as the possibility of medical data utilization by domestic bio-health companies expands, along with the policy conversion of the "Data 3 Act" passed by the National Assembly in January 2019.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.795-813
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• 2001

Sophisticated geometric structure analysis must be preceded to create electronic document from logical components extracted from document image. this paper presents a knowledge-based method for sophisticated geometric structure analysis of technical journal pages. The proposed knowledge base encodes geometric characteristics that are not only common in technical journals but also publication-specific in the form rules. The method takes the hybrid of top-down and bottom-up techniques and consists of two phases: region segmentation and identification. Generally, the result of segmentation process does not have a one-to-one matching with composite layout components. Therefore, the proposed method identifies non-text objects such as image, drawing and table, as well as text objects such as text line and equation by splitting or grouping segmented regions into composite layout components. Experimental results with 372 images scanned from the IEEE Transactions on Pattern Analysis and Machine Intelligence show that the proposed method has performed geometrical structure analysis successfully on more than 99% of the test images, resulting in sophisticated performance compared with previous works.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.364-371
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• 2021

Public awareness of alien species can vary by generation, period, or specific events associated with these species. An understanding of public awareness is important for the management of alien species because differences in public awareness can affect the establishment and implementation of management plans. We analyzed digital texts on social media platforms, news articles, and internet search volumes used in conservation culturomics to understand public interest and sentiment regarding alien freshwater species. The number of tweets, number of news articles, and relative search volume to 11 freshwater alien species were extracted to determine public interest. Additionally, the trend over time, seasonal variability, and repetition period of these data were confirmed. We also calculated the sentiment score and analyzed public sentiment in the collected data using sentiment analysis based on text mining techniques. The American bullfrog, nutria, bluegill, and largemouth bass drew relatively more public interest than other species. Some species showed repeated patterns in the number of Twitter posts, media coverage, and internet searches found according to the specified periods. The text mining analysis results showed negative sentiments from most people regarding alien freshwater species. Particularly, negative sentiments increased over the years after alien species were designated as ecologically disturbing species.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.499-507
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• 2007

In the areas of CAE, CAD and CAO integration & automation technology, the word 'File Wrapping' means a virtualization of TEXT files that supports variables-based I/Os like variable assignments in programming languages. This File Wrapping process is one of the cornerstones of CAE, CAD and GAO integration & automation, and the performance of File Wrapping process, which is depending on the sire of a TEXT file to be accessed and the number of regions and their distribution, has a critical effect on the total performance of the CAE, CAD and CAO integration & automation systems. In this paper, we define TEXT File Region Management which generalizes the main functions of the File Wrapping process, and describe a prototype of TEXT file Region Management which is implemented as a Grid service. After that, the validity of the proposed model and the TEXT File Region Management service are discussed with evaluation results of the prototype.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.545-556
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• 2013

This study has established the GUI design elements of mobile phones as color, text, layout, graphic icon, and video, under the purpose of exploring the relevance between such elements and brand preference among senior citizens. To accomplish the objective, a model and hypotheses were established, which were tested through a multiple regression analysis. The findings are as follows. First, when the statistical significance was examined by GUI design element of mobile phones, the following results were obtained: Color, text, layout, graphic icon, and video were statistically significant at the significance level given, indicating that such elements all affect brand preference. Second, the relative influence of GUI design elements of mobile phones on brand preference was revealed in the following order: text, color, video, graphic icon, layout. It indicates that boosting the brand preference of senior citizens for mobile phones requires considering 'text' and 'color' first before any other element. In addition, as the influence of 'text' and 'color' becomes greater, the brand preference also becomes higher.

• Korean Journal of Cognitive Science
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• v.24 no.4
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• pp.301-321
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• 2013

For the task of sentence ordering, this paper attempts to utilize the Entity-Grid model, a type of entity-based modeling approach, as well as Latent Semantic analysis, which is based on vector space modeling, The task is well known as one of the fundamental tools used to measure text coherence and to enhance text generation processes. For the implementation of the Entity-Grid model, we attempt to use the syntactic roles of the nouns in the Korean text for the ordering task, and measure its impact on the result, since its contribution has been discussed in previous research. Contrary to the case of German, it shows a positive result. In order to obtain the information on the syntactic roles, we use a strategy of using Korean case-markers for the nouns. As a result, it is revealed that the cues can be helpful to measure text coherence. In addition, we compare the results with the ones of the LSA-based model, discussing the advantages and disadvantages of the models, and options for future studies.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1649-1659
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• 2004

Text Generation is a process of generating comprehensible texts in human languages from some underlying non-linguistic representation of information. Among several sub-processes for text generation to generate coherent texts, this paper concerns referring expression generation which produces different types of expressions to refer to previously-mentioned things in a discourse. Specifically, we focus on pronominalization by zero pronouns which frequently occur in Korean. To build a generation model of referring expressions for Korean, several features are identified based on grammatical information and cost-based centering model, which are applied to various machine learning techniques. We demonstrate that our proposed features are well defined to explain pronominalization, especially pronominalization by zero pronouns in Korean, through 95 texts from three genres - Descriptive texts, News, and Short Aesop's Fables. We also show that our model significantly outperforms previous ones with a 99.9% confidence level by a T-test.