• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.520-530
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• 2020

The purpose of this study was to investigate students' understanding of the terms presented on the information board in the Jinan-Muju National Geopark. To this end, a survey was conducted with 219 students (147 elementary, 41 middle, and 31 high school students) to determine the level of their perceptions of the geopark, and of the usefulness of the information board, and their understanding of the terms presented on the information boards of the National Geopark. To determine the students' understanding of terms, 10 representative information boards were selected and the entire content was converted into text. Afterwards, 256 key terms were extracted from the text through discussions with three experts, and these terms were presented to students to grasp their level of understanding. The results were as follows: First, the level of students' perceptions about the geopark was very low, so publicity and educational approaches are needed. Second, students were not interested in the information board and had a low level of understanding owing to the large amount of information and reading difficulties. Third, among the 256 terms, the number of terms that students found difficult to understand tended to decrease with increasing school grade: 80 for elementary school students, 53 for middle school students, and 31 for high school students. The reason the students had difficulty in understanding terms was that elementary school students had not yet learned the terms in the curriculum, whereas middle and high school students have difficulty understanding technical terms and Chinese characters. Therefore, the information board in the geopark will need to be easily translated into Chinese characters or additional explanations of technical terms need to be provided so that visitors can understand the concepts more easily.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.55-63
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• 2020

Recently, there is a strong interest in SW basic education for non-major students in universities, but SW non-majors are having a hard time learning. This paper proposes a class operation method that utilizes customized contents reflecting the interests of non-majors, rather than using existing learning contents for SW majors. The proposed method is to improve the education effects by increasing the learning motivation of SW non-majors. The paper shows a case study of A university, which has operated non-major SW basic education for more than five years. The case study analyzed the change of class satisfaction of students of pre- and post- learning group that reformed major-friendly contents about the same curriculum. As a result, the students of social sciences are interested in learning contents using public data that can examine the social and cultural phenomena of the country, and humanities students are interested in text contents such as novels, history books, and SNS articles. In addition to the understanding of the lectures, the class satisfaction was also greatly improved, and it showed that the major-friendly contents is useful for SW basic education of non-majors.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.21-32
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• 2010

This study investigated the effects of contiguity and reading mode on cognitive load factors measured by Galvanic Skin Response(GSR). In this study two experimental conditions were imposed to participants to measure cognitive load with the high contiguity picture and low contiguity picture. Thirty-four college students participated to this experiment(experiment group=17, control group=17), and spilt-plot factorial design was applied to control individual difference in galvanic skin response. Tasks of this experiment were reading and summary. The dependent variables were skin conductance response, and perceived difficulty. The independent variables were the degree of contiguity of visual material(high contiguity vs. low contiguity). The major result of this study was identification of a significant difference of GSR with low contiguity condition. Indeed it was identified that more complex reading condition required more cognitive loads. This finding supported that different cognitive process might require different amounts of cognitive loads. For the further research, this study discussed the validity of applying physiological signals to assess cognitive loads and relationships the associated affective reactions.

• Korean journal of communication and information
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• v.60
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• pp.104-124
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• 2012

The purpose of this study is to explore how North Korean woman defectors' memories of their past lives are represented in Korean television talk show, (Channel A, 2011~) and its social implications. In order to carry out this task, this study first discusses the emergence of the concept of 'memory' in its relations with 'collective memory', 'cultural memory' and 'history', and its social appropriation in media such as television. And, the ideological aspects of the recent trend of television talk show that deals with people's private memories were also discussed. The study used the method of structural narrative analysis. The findings are the following. First of all, North Korean woman defectors' memories in collide with the dominant public memories in South Korea. In any case, it has been found that the show tended to make North Korea and their defectors as exotic 'others' and thereby reinforce the existing public memory. After all, this study argues that the representation of the defectors' memories in the talk show only results in stressing the melodramatic narrative emotionally packaged with 'laughing' and 'crying' without any sincere consideration of them.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.5
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• pp.1-11
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• 2016

There has been an increasingly high interest in gardens and garden design in Korea recently. However, the usage of the term 'garden' is extremely varied and complex, and there has been very little academic research made on the meaning of garden. Therefore, this research attempts to investigate the ideas of current gardens and to elucidate their changing patterns by means of extensive literature research and big data analysis. The notion of garden in the past was broad including not only private space such as Madang(마당) and Teul(뜰), but also even field and grass land as public outdoor space. Yet, the meaning has become smaller to merely private space due to the change of dwelling systems due to high industrial development of the 20th century. Furthermore, the introduction of urban parks as an interactive space between nature and humans, the similar spatial function of gardens, has blurred the boundary between garden and park, which created confusion in understanding the concept of a garden. After all, garden is a subject for humans. The meanings of garden need to be recognized from various points of view since garden itself is a creation by the sum of diverse fields such as natural and social sciences as well as culturology. This discussion on the meaning of garden in the present day will give a conceptual foundation for future research on gardens and garden design. Also, the big data analysis employed here as a research method can help other similar research topics, particularly semantics in landscape architecture.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.406-415
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• 2005

Prosperity of Internet led to the web containing huge number of documents. Thus increasing importance is given to the web information retrieval technology that can provide users with documents that contain the right information they want. This paper proposes several techniques that are effective for the improvement of web information retrieval. Similarity between a document and the query is a major source of information exploited by conventional systems. However, we suggest a technique to make use of similarity between a sentence and the query. We introduce a technique to compute the approximate score of the sentence-query similarity even without a mature technology of natural language processing. It was shown that the amount of computation for this task is linear to the number of documents in the total collection, which implies that practical systems can make use of this technique. The next important technique proposed in this paper is to use stratification of documents in re-ranking the documents to output. It was shown that it can lead to significant improvement in performance. We furthermore showed that using hyper links, anchor texts, and titles can result in enhancement of performance. To justify the proposed techniques we developed a large scale web information retrieval system and used it for experiments.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1193-1203
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• 1999

본 논문에서는 한글과 영문 문서 영상들에 대한 기울어짐 추정(skew estimation) 알고리즘을 제안한다. 제안 방법은 전체 문서 영상에서 텍스트 요소들이 밀집되어 있는 영역을 선별하고, 선별된 영역에 대해 허프 변환을 적용하는 선택적 주의집중(selective attention) 방식을 채택한다. 제안 방법의 기울기 추정 과정은 2단계로 구성되는데, coarse 단계에서는 전체 영상을 몇 개의 영역으로 나누고 동일한 영역에 속하는 데이타들간의 연결 각도를 계산하여 각 영역별 accumulator에 저장한다. accumulator에 저장된 빈도치를 기준으로 $\pm$45$^{\circ}$범위 내에서 최대 $\pm$1$^{\circ}$의 오차를 가진 각 영역별 기울기를 계산한 후, 이들 중 최대 빈도값을 갖는 영역을 선정하고 그 영역의 기울기 각도를 문서 영상의 대략적인 기울기 각도로 결정한다. Refine 단계에서는 coarse 단계에서 선정된 영역에 허프 변환을 적용하여 정확한 기울기를 계산하는데, coarse 단계에서 추정한 기울기의 $\pm$1$^{\circ}$범위 내에서 0.1$^{\circ}$간격으로 측정한다. 이와 같은 선택적 주의집중 방식을 통해 기울기 추정에 소요되는 시간 비용은 최소화하고, 추정의 정확도는 최대화 할 수 있다.제안 방법의 성능 평가를 위한 실험은 다양한 형태의 영문과 한글 문서 영상 2,016개에 적용되었다. 제안 방법의 평균 수행 시간은 Pentium 200MHz PC에서 0.19초이고 평균 오차는 $\pm$0.08$^{\circ}$이다. 또한 기존의 기울기 추정 방법과 제안 방법의 성능을 비교하여 제안 방법의 우수성을 입증하였다.Abstract In this paper we propose a skew estimation algorithm for English and Korean document images. The proposed method adopts a selective attention strategy, in which we choose a region of interest which contains a cluster of text components and then apply a Hough transform to this region. The skew estimation process consists of two steps. In the coarse step, we divide the entire image into several regions, and compute the skew angle of each region by accumulating the slopes of lines connecting any two components in the region. The skew angle is estimated within the range of $\pm$45 degree with a maximum error of $\pm$1 degree. Next we select a region which has the most frequent slope in the accumulators and determine the skew angle of the image roughly as the angle corresponding to the most frequent slope. In the refine step, a Hough transform is applied for the selected region within the range of $\pm$1 degree along the angle computed from the coarse step, with an angular resolution of 0.1 degree. Based on this selective attention strategy, we can minimize the time cost and maximize the accuracy of the skew estimation.We have measured the performance of the proposed method by an experiment with 2,016 images of various English and Korean documents. The average run time is 0.19 second on a Pentium 200MHz PC, and the average error is $\pm$0.08 degree. We also have proven the superiority of our algorithm by comparing the performance with that of other well-known methods in the literature.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1204-1218
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• 1999

문서영상 검색을 위한 디지털도서관의 대부분은 논문제목과/또는 논문요약으로부터 만들어진 색인에 근거한 제한적인 검색기능을 제공하고 있다. 본 논문에서는 영문 문서영상전체에 대한 검색을 위한 단어 영상 형태 특징기반의 단어검색시스템을 제안한다. 본 논문에서는 검색의 효율성과 정확도를 높이기 위해 1) 기존의 단어검색시스템에서 사용된 특징들을 조합하여 사용하며, 2) 특징의 개수 및 위치뿐만 아니라 특징들의 순서를 포함하여 매칭하는 방법을 사용하며, 3) 특징비교에 의해 검색결과를 얻은 후에 여과목적으로 문자인식을 부분적으로 적용하는 2단계의 검색방법을 사용한다. 제안된 시스템의 동작은 다음과 같다. 문서 영상이 주어지면, 문서 영상 구조가 분석되고 단어 영역들의 조합으로 분할된다. 단어 영상의 특징들이 추출되어 저장된다. 사용자의 텍스트 질의가 주어지면 이에 대응되는 단어 영상이 만들어지며 이로부터 영상특징이 추출된다. 이 참조 특징과 저장된 특징들과 비교하여 유사한 단어를 검색하게 된다. 제안된 시스템은 IBM-PC를 이용한 웹 환경에서 구축되었으며, 영문 문서영상을 이용하여 실험이 수행되었다. 실험결과는 본 논문에서 제안하는 방법들의 유효성을 보여주고 있다. Abstract Most existing digital libraries for document image retrieval provide a limited retrieval service due to their indexing from document titles and/or the content of document abstracts. This paper proposes a word spotting system for full English document image retrieval based on word image shape features. In order to improve not only the efficiency but also the precision of a retrieval system, we develop the system by 1) using a combination of the holistic features which have been used in the existing word spotting systems, 2) performing image matching by comparing the order of features in a word in addition to the number of features and their positions, and 3) adopting 2 stage retrieval strategies by obtaining retrieval results by image feature matching and applying OCR(Optical Charater Recognition) partly to the results for filtering purpose. The proposed system operates as follows: given a document image, its structure is analyzed and is segmented into a set of word regions. Then, word shape features are extracted and stored. Given a user's query with text, features are extracted after its corresponding word image is generated. This reference model is compared with the stored features to find out similar words. The proposed system is implemented with IBM-PC in a web environment and its experiments are performed with English document images. Experimental results show the effectiveness of the proposed methods.

• Journal of KIISE
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• v.42 no.4
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• pp.451-458
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• 2015

Previous multimodal learning methods focus on problem-solving aspects, such as image and video search and tagging, rather than on knowledge acquisition via content modeling. In this paper, we propose the Multimodal Concept Hierarchy (MuCH), which is a content modeling method that uses a cartoon video dataset and a character-based subtitle generation method from the learned model. The MuCH model has a multimodal hypernetwork layer, in which the patterns of the words and image patches are represented, and a concept layer, in which each concept variable is represented by a probability distribution of the words and the image patches. The model can learn the characteristics of the characters as concepts from the video subtitles and scene images by using a Bayesian learning method and can also generate character-based subtitles from the learned model if text queries are provided. As an experiment, the MuCH model learned concepts from 'Pororo' cartoon videos with a total of 268 minutes in length and generated character-based subtitles. Finally, we compare the results with those of other multimodal learning models. The Experimental results indicate that given the same text query, our model generates more accurate and more character-specific subtitles than other models.