• Title/Summary/Keyword: category classification

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Decomposition of category mixture in a pixel and its application for supervised image classification

  • Matsumoto, Masao;Arai, Kohei;Ishimatsu, Takakazu
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.514-519
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    • 1992
  • To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

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Category Factor Based Feature Selection for Document Classification

  • Kang Yun-Hee
    • International Journal of Contents
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    • v.1 no.2
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    • pp.26-30
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    • 2005
  • According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

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The vegetation analysis of Northern region at Jungnang riverside - Between two bridges of Wallgae 1 and Sangdo - (서울시 중랑천 북부구간 하천변 식생과 식물상 분석 - 월계1교에서 상도교 구간을 대상으로 -)

  • Lee, Sanghwa;Lee, Kyunghee;Jeong, Jongcheol
    • Journal of Environmental Impact Assessment
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    • v.23 no.4
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    • pp.315-322
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    • 2014
  • After the modern industrial revolution, rivers in cities became covered and disappeared due to the pressure to develop them. Likewise, their function which is to serve as the basis of natural ecology system in the cities began to be damaged. This research demonstrated that there are a total of 268 categories when it comes to the list of plants, including 64 families, 179 genera, 230 species, 36 varieties, and 1 subspecies. When the relative abundance of the plants that were found at the target research site was studied, the secondary survey demonstrated Bromus japonicus 22.97, Artemisia princeps var. orientalis 16.76 and Erigeron annuus 15.69 while third survey demonstrated Digitaria ciliaris 26.78, Ambrosia trifida 16.29 and Aster pilosus 14.31. There were 54 species of naturalized plants that appeared. Analysis demonstrated annual plant 23 classification category (43%), perennial 11 classification category (20%), multi-perennation 17 classification category (31%), woody plant 3 classification category (6%) and others. When the naturalized plants that were found at the target research site were analyzed by the place of origin, North America and EU took up 76%, which accounts for 3/4 of the all the naturalized plants. At the target research site, naturalization degree of 5 pertained to 22 classification category (41%), which was the highest, followed by 19 classification category (35%) with naturalization degree of 3, 8 classification category (15%) with naturalization degree of 2 and 5 classification category (9%) with naturalization degree of 4 in the order mentioned. Flora of Jungnangcheon did not manifest any change compared to 10 years ago. Thus, it is necessary to increase of biodiversity efforts to improve SeoulCity's natural environment and cityscape.

Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information

  • Oh, Heung-Seon;Jung, Yuchul
    • Journal of Information Science Theory and Practice
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    • v.5 no.3
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    • pp.31-47
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    • 2017
  • The narrow-down approach, separately composed of search and classification stages, is an effective way of dealing with large-scale hierarchical text classification. Recent approaches introduce methods of incorporating global, local, and path information extracted from web taxonomies in the classification stage. Meanwhile, in the case of utilizing path information, there have been few efforts to address existing limitations and develop more sophisticated methods. In this paper, we propose an expansion method to effectively exploit category path information based on the observation that the existing method is exposed to a term mismatch problem and low discrimination power due to insufficient path information. The key idea of our method is to utilize relevant information not presented on category paths by adding more useful words. We evaluate the effectiveness of our method on state-of-the art narrow-down methods and report the results with in-depth analysis.

Study on Application of IUCN Management Category System on Baekdudaegan Protected Area (백두대간보호지역의 IUCN 관리 카테고리 적용 연구)

  • Kim, Seongil;Kang, Mihee
    • Journal of Korean Society of Forest Science
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    • v.100 no.3
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    • pp.494-503
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    • 2011
  • This study was aimed at applying the IUCN category system to the Baekdudaegan Protected Area. A classification key was developed to apply the system to the overlapped designated protected areas inside of Baekdudaegan Protected Area. Korea national parks and forests managers' and experts' opinions were collected and they all agreed to the use of multiple classification in Baekdudaegan Protected Area. For example, the type of natural forests among the Forest Genetic Resources Reserves was classified to be IUCN Category Ia while other types of Forest Genetic Resources Reserve was classified to be Category IV. And the Protected Forest Landscape was classified to be Category V while the other types of protected forests were classified to be Category VI. The study suggests the need of classification of forest protected areas including Baekdudaegan Protected Area using IUCN system accompanying with protected areas management effectiveness evaluation.

Pattern Classification of Multi-Spectral Satellite Images based on Fusion of Fuzzy Algorithms (퍼지 알고리즘의 융합에 의한 다중분광 영상의 패턴분류)

  • Jeon, Young-Joon;Kim, Jin-Il
    • Journal of KIISE:Software and Applications
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    • v.32 no.7
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    • pp.674-682
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    • 2005
  • This paper proposes classification of multi-spectral satellite image based on fusion of fuzzy G-K (Gustafson-Kessel) algorithm and PCM algorithm. The suggested algorithm establishes the initial cluster centers by selecting training data from each category, and then executes the fuzzy G-K algorithm. PCM algorithm perform using classification result of the fuzzy G-K algorithm. The classification categories are allocated to the corresponding category when the results of classification by fuzzy G-K algorithm and PCM algorithm belong to the same category. If the classification result of two algorithms belongs to the different category, the pixels are allocated by Bayesian maximum likelihood algorithm. Bayesian maximum likelihood algorithm uses the data from the interior of the average intracluster distance. The information of the pixels within the average intracluster distance has a positive normal distribution. It improves classification result by giving a positive effect in Bayesian maximum likelihood algorithm. The proposed method is applied to IKONOS and Landsat TM remote sensing satellite image for the test. As a result, the overall accuracy showed a better outcome than individual Fuzzy G-K algorithm and PCM algorithm or the conventional maximum likelihood classification algorithm.

Hierarchical Automatic Classification of News Articles based on Association Rules (연관규칙을 이용한 뉴스기사의 계층적 자동분류기법)

  • Joo, Kil-Hong;Shin, Eun-Young;Lee, Joo-Il;Lee, Won-Suk
    • 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 Effect of the classification problem solving of Thinking Science Program on the Classified Activities on Elementary School 5th grade category (Thinking Science 프로그램 중 분류활동이 초등학교 5학년 학생의 분류문제해결능력에 미치는 영향)

  • Lee, Sung-Hyun;Han, Shin
    • Journal of the Korean Society of Earth Science Education
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    • v.4 no.2
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    • pp.102-107
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    • 2011
  • In this study, elementary school science program, this category did not affect any troubleshooting analyzed. Thinking Science Program to buy for them in group activities by using one of the elements of a program of treatment and cognitive level effects were two kinds of research questions. 102, 5th grade four classes were involved, these two classes of the experimental group and the remaining two classes were divided into a control group. Pre-test between the two groups is compared to the level and classification problem-solving skills but the skills did not show a statistically significant difference. Thinking Science activity after application of classification and posttest the experimental group than in the control group problem solving abilities of students classified at the level of statistical significance was higher. Thinking Science program is a treatment effect for each level of analysis, tests, regardless of cognitive level was more effective. Through theses findings, Thinking Science activities 5th grade category classification problem-solving skills of students found to be effective in improving and these types of programs actively introduced in the field suggests that we need to see.

A Three-Step Preprocessing Algorithm for Enhanced Classification of E-Mail Recommendation System (이메일 추천 시스템의 분류 향상을 위한 3단계 전처리 알고리즘)

  • Jeong Ok-Ran;Cho Dong-Sub
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.4
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    • pp.251-258
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    • 2005
  • Automatic document classification may differ significantly according to the characteristics of documents that are subject to classification, as well as classifier's performance. This research identifies e-mail document's characteristics to apply a three-step preprocessing algorithm that can minimize e-mail document's atypical characteristics. In the first 5go, uncertain based sampling algorithm that used Mean Absolute Deviation(MAD), is used to address the question of selection learning document for the rule generation at the time of classification. In the subsequent stage, Weighted vlaue assigning method by attribute is applied to increase the discriminating capability of the terms that appear on the title on the e-mail document characteristic level. in the third and last stage, accuracy level during classification by each category is increased by using Naive Bayesian Presumptive Algorithm's Dynamic Threshold. And, we implemented an E-Mail Recommendtion System using a three-step preprocessing algorithm the enable users for direct and optimal classification with the recommendation of the applicable category when a mail arrives.

Tendency of Elementary School Pupils' Classification Ability Development (초등학생 분류능력 발달의 경향성)

  • Choi Ryun-Dong;Yang Il-Ro;Kwon Chi-Soon
    • Journal of Korean Elementary Science Education
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    • v.24 no.3
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    • pp.281-291
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    • 2005
  • The purpose of this study was to investigate elementary school pupil's classification ability that appears in classification activity. For this study, we developed 2 suitable tools in classification activity achievement. One is artificial stimulus card that comes into view clearly. The other is natural stimulus card that does not come into view well. The test was administrated to 376 pupils of 2, 4, and 6 grade in D elementary School in Yeongdeungpo-gu, Seoul. The result proved in this study was as following. First, elementary school pupil's classification ability showed the developmental change as the grade level rises. Second, there was no statistical difference between boys and girls. Third, there was high correlation between sort artificial category and natural category in their ability. Fourth, classification achievement rate of constant level by grade was seen regardless of the items. The findings above gives following guidance in science classification learning. First, if teacher understands the development of students' classification ability, more effective classification guidance is available. Second, to cultivate students' classification ability, we should devise and apply program depending on their classification ability by grade.

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