• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.703-714
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• 2005

Researches in text categorization have been confined to whole-document-level classification, probably due to lacks of full-text test collections. However, full-length documents availably today in large quantities pose renewed interests in text classification. A document is usually written in an organized structure to present its main topic(s). This structure can be expressed as a sequence of sub-topic text blocks, or passages. In order to reflect the sub-topic structure of a document, we propose a new passage-level or passage-based text categorization model, which segments a test document into several Passages, assigns categories to each passage, and merges passage categories to document categories. Compared with traditional document-level categorization, two additional steps, passage splitting and category merging, are required in this model. By using four subsets of Routers text categorization test collection and a full-text test collection of which documents are varying from tens of kilobytes to hundreds, we evaluated the proposed model, especially the effectiveness of various passage types and the importance of passage location in category merging. Our results show simple windows are best for all test collections tested in these experiments. We also found that passages have different degrees of contribution to main topic(s), depending on their location in the test document.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.503-507
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• 2001

최근 개발되고 있는 SAN 기반 리눅스 클러스터 파일 시스템들은 중앙에 파일 서버 없이 디스크를 공유하는 클라이언트들이 화이버 채널을 통하여 마치 파일 서버처럼 디스크에 자유롭게 접근할 수 있으므로, 유용성, 부하의 균형, 확장성 등에서 장점을 가진다. 본 논문에서는 ETRI에서 개발중인 SAN 기반 리눅스 클러스터 파일 시스템인 SANtopia를 위해 설계된 새로운 mode의 구조와 이 inode의 구조를 기반으로 확장 해싱(Extendible Hashing)을 이용한 새로운 디렉토리 구조의 설계에 대하여 기술하고,성능 평가를 통하여 제안된 방법의 우수성을 보인다.

• Proceedings of the Korean DIstribution Association Conference
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• 1997.07a
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• pp.81-100
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• 1997

현재 국내의 유통업계 전반에 걸친 대변혁은 유통업에 참여하고 기업뿐만 아니라 가치전달기능의 최종 목적지인 소비자, 유통정책을 수립하고 추진하는 정부, 유통체제의 일원인 제조업체 등 관련 이익집단에 유통 기능을 수행하는 마케팅에 대한 새로운 이해의 필요성을 강조하고 있다. 여기서 말하는 새로운 이채란 각 기업과 연관하여 파악된 마케팅 활동의 범주를 넘어 다수의 마케팅 연관 기관의 유기적 교류로 이루어진 마케팅 시스템과 사회의 연관 관계에 대한 이해로 정의 할 수 있을 것이다.(중략)

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.214-221
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• 2010

The search-results clustering problem is defined as the automatic and on-line grouping of similar documents in search results returned from a search engine. In this paper, we propose a new search-results clustering algorithm specialized for a paper search service. Our system consists of two algorithmic phases: Category Hierarchy Generation System (CHGS) and Paper Clustering System (PCS). In CHGS, we first build up the category hierarchy, called the Field Thesaurus, for each research field using an existing research category hierarchy (KOSEF's research category hierarchy) and the keyword expansion of the field thesaurus by a word clustering method using the K-means algorithm. Then, in PCS, the proposed algorithm determines the category of each paper using top-down and bottom-up methods. The proposed system can be used in the application areas for retrieval services in a specialized field such as a paper search service.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.157-164
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• 2015

This paper describes subspace clustering of categorical data for convergence and integration. Because categorical data are not designed for dealing only with numerical data, The conventional evaluation measures are more likely to have the limitations due to the absence of ordering and high dimensional data and scarcity of frequency. Hence, conditional entropy measure is proposed to evaluate close approximation of cohesion among attributes within each cluster. We propose a new objective function that is used to reflect the optimistic clustering so that the within-cluster dispersion is minimized and the between-cluster separation is enhanced. We performed experiments on five real-world datasets, comparing the performance of our algorithms with four algorithms, using three evaluation metrics: accuracy, f-measure and adjusted Rand index. According to the experiments, the proposed algorithm outperforms the algorithms that were considered int the evaluation, regarding the considered metrics.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.730-741
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• 2011

With the development of the internet and computer technology, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The conventional document categorization method used only the keywords of related documents for document classification. However, this paper proposed keyword extraction method of based on association rule. This method extracts a set of related keywords which are involved in document's category and classifies representative keyword by using the classification rule proposed in this paper. In addition, this paper proposed the preprocessing method for efficient keywords creation and predicted the new document's category. We can design the classifier and measure the performance throughout the experiment to increase the profile's classification performance. When predicting the category, substituting all the classification rules one by one is the major reason to decrease the process performance in a profile. Finally, this paper suggested automatically categorizing plan which can be applied to hierarchical category architecture, extended from simple category architecture.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.615-632
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• 2017

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. The matching with the propensity score is one of the most popular methods to control the confounders in order to evaluate the effect of the treatment on the outcome variable. Recently, new methods for the causal inference in latent class analysis (LCA) have been proposed to estimate the average causal effect (ACE) of the treatment on the latent discrete variable. They have focused on the application study for the real dataset to estimate the ACE in LCA. In practice, however, the true values of the ACE are not known, and it is difficult to evaluate the performance of the estimated the ACE. In this study, we propose a method to generate a synthetic data using the propensity score in the framework of LCA, where treatment and outcome variables are latent. We then propose a new method for estimating the ACE in LCA and evaluate its performance via simulation studies. Furthermore we present an empirical analysis based on data form the 'National Longitudinal Study of Adolescents Health,' where puberty as a latent treatment and substance use as a latent outcome variable.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.646-654
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• 2006

Directory searching and index searching methods are two main methods in web search engines. Both of the methods are applied to most of the well-known Internet search engines, which enable users to choose the other method if they are not satisfied with results shown by one method. That is, Index searching tends to come up with too many search results, while directory searching has a difficulty in selecting proper categories, frequently mislead to false ones. In this paper, we propose a novel method in which a category hierarchy is dynamically constructed. To do this, a category is regarded as a fuzzy set which includes keywords. Similarly extensible subcategories of a category can be found using fuzzy relational products. The merit of this method is to enhance the recall rate of directory search by expanding subcategories on the basis of similarity.

• Journal of Gifted/Talented Education
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• v.25 no.2
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• pp.321-337
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• 2015

The purpose of the present study is to examine elementary gifted students' perceptions on bias against creativity utilizing concept mapping approach. Twelve elementary gifted students participated in the group brainstorming and produced 55 final statements. Based on these statements, the multi-dimensional scale and hierarchial cluster analysis using dissimilarity matrix were performed. Average stress value was .30 which is appropriate for a two-dimensional concept mapping study. In addition, a questionnaire survey using likert 6 points scale was carried out targeting 132 elementary gifted students to analyze the degree of sympathy on their anti-creativity bias perception. The findings are as follow: First, four categories were concluded dividing gifted students' perceptions on bias against creativity from the hierarchial cluster analysis with X-Y coordinate matrix, these were 'Contradictory attitudes to creativity', 'Low evaluation for creativity', 'Forced to predetermined rules and ideas', and 'Aversion to new things'. Second, elementary gifted students were sympathetic to the order 'Forced to predetermined rules and ideas'(M=4.16), 'Aversion to new things'(M=3.68), 'Contradictory attitudes to creativity'(M=3.55) and 'Low evaluation for creativity'(M=3.30). This study aims to examine, analyze and categorize various relevant factors related to elementary gifted students' perceptions on bias against creativity. Implications of the study related to the present and future creative education were discussed in depth.

• Journal of the KSME
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• v.20 no.2
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• pp.123-130
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• 1980

산업용로보트는 보통의 자동 기계와는 달리 상대하는 대상물과의 위치적 관계가 중요하여, 시 시각각으로 변화하는 대상물의 위치정보를 로보트 자체의 구동에 반영하여야 한다. 따라서 종 래의 써보 메카니즘(Servomechanism)의 제어 기술에서 보다 고려되어야할 사항이 많으며 제어 방법자체도 기능 제어(Intelligent Control) 분야라는 새로운 범주에 속하여 활발한 연구가 되고 있다. 본문에서는 이러한 산업용로보트의 제어기술에 관하여 기술하기로 한다.