• The Mathematical Education
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• v.24 no.2
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• pp.105-116
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• 1986

For any thought and knowledge, its growth and development has close relation with the society where it is developed and grow. As Feuerbach says, the birth of spirit needs an existence of two human beings, i. e. the social background, as well as the birth of body does. But, at the educational viewpoint, the spread and the growth of such a thought or knowledge that influence favorably the development of a society must be also considered. We would discuss the goal and the function of mathematics education in relation with the prosperity of a technological civilization. But, the goal and the function are not unrelated with the spiritual culture which is basis of the technological civilization. Most societies of today can be called open democratic societies or societies which are at least standing such. The concept of rationality in such societies is a methodological principle which completes the democratic society. At the same time, it is asserted as an educational value concept which explains comprehensively the standpoint and the attitude of one who is educated in such a society. Especially, we can considered the cultivation of a mathematical thinking or a logical thinking in the goal of mathematics education as a concept which is included in such an educational value concept. The use of the concept of rationality depends on various viewpoints and criterions. We can analyze the concept of rationality at two aspects, one is the aspect of human behavior and the other is that of human belief or knowledge. Generally speaking, the rationality in human behavior means a problem solving power or a reasoning power as an instrument, i. e. the human economical cast of mind. But, the conceptual condition like this cannot include value concept. On the other hand, the rationality in human knowledge is related with the problem of rationality in human belief. For any statement which represents a certain sort of knowledge, its universal validity cannot be assured. The statements of value judgment which represent the philosophical knowledge cannot but relate to the argument on the rationality in human belief, because their finality do not easily turn out to be true or false. The positive statements in science also relate to the argument on the rationality in human belief, because there are no necessary relations between the proposition which states the all-pervasive rule and the proposition which is induced from the results of observation. Especially, the logical statement in logic or mathematics resolves itself into a question of the rationality in human belief after all, because all the logical proposition have their logical propriety in a certain deductive system which must start from some axioms, and the selection and construction of an axiomatic system cannot but depend on the belief of a man himself. Thus, we can conclude that a question of the rationality in knowledge or belief is a question of the rationality both in the content of belief or knowledge and in the process where one holds his own belief. And the rationality of both the content and the process is namely an deal form of a human ability and attitude in one's rational behavior. Considering the advancement of mathematical knowledge, we can say that mathematics is a good example which reflects such a human rationality, i. e. the human ability and attitude. By this property of mathematics itself, mathematics is deeply rooted as a good. subject which as needed in moulding the ability and attitude of a rational person who contributes to the development of the open democratic society he belongs to. But, it is needed to analyze the practicing and pursuing the rationality especially in mathematics education. Mathematics teacher must aim the rationality of process where the mathematical belief is maintained. In fact, there is no problem in the rationality of content as long the mathematics teacher does not draw mathematical conclusions without bases. But, in the mathematical activities he presents in his class, mathematics teacher must be able to show hem together with what even his own belief on the efficiency and propriety of mathematical activites can be altered and advanced by a new thinking or new experiences.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.23-33
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• 2016

The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• The Journal of Korean Society for School & Community Health Education
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• v.1 no.1
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• pp.11-43
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• 2000

The purpose of this study was, through analyzing the previous researches, to grasp the present status of environment of school building(ESB), research the sundry records of each element and, through comparative analysis of the standard of ESB in Korea, the United States, and Japan, select the normative standard of ESB, to clarify the point at issue presented in Regulation of Construction & facility Management for Elementary and and Secondary School in Korea, and to suggest an alternative preliminary standard of ESB. To carry out a research for this purpose, these were required: 1. to investigate the existing present status of ESB, 2. to make a comparative analysis of the standard of ESB in each country, 3. to suggest the normative standard of preliminary standard of ESB, 4. to analyze the controversial points of the standard of ESB in Korea, 5. to suggest an alternative preliminary standard of ESB. The conclusions were as follows: 1. Putting, through analyzing the previous researches, the existing present status of ESB together, it seemed that lighting environment, indoor air environment and noise environment were all in poor conditions. 2. In the result of a comparative analysis of the standard of ESB in Korea, Japan and the United States, in Korea the factors of each lighting and indoor air environment were not presented properly, in Japan, in lighting environment aspect, the standard on natural lighting and the factors on brightness were not presented., and in the USA the essential factors of each environment were throughly presented. In the comparison of the standards on each factor, Korea showed that the standard level presented was less properly prescribed than those of the USA and Japan but it also showed that the standard levels prescribed in the USA and in Japan were mostly similar to the standard levels in records investigated. 3. With the result of the normative standard selection on School Builiding environment factor of prescribed in this study, the controversial points of the standard of ESB in Korea were analyzed and the result was utilized to suggest new preliminary standard of ESB. 4. As the result of the analysis of the controversial points of the standard of ESB in Korea, it was found that the standard of ESB in Korea should be established on a basis of School Health Act and be concretely presented in School Health Regulation and School Health Rule. The factors of each environment was improperly presented in the existing standard of ESB in Korea. Moreover the standard of them was inferior to that of the records investigated and those of in the USA and in Japan and it also showed that the standard of it in Korea was improper to maintain Comfortable Learning Environment. 5. A suggested preliminary standard of ESB acquired through above study as follows: 1) In this study a new kind of preliminary standard of ESB is divided into lighting environment, indoor air environment, noise environment, odor environment and for above classification, reasonable factor and standard should be established and the controling way on each standard and countermeasures against it should be considered. 2) In lighting environment, the factors of natural lighting are divided into daylight rate, brightness, glare. In the standard on each factor, daylight rate should secure 5% of a mean daylight rate and 2% of a minimum daylight rate, brightness ratio of maximum illumination to minimum illumination should be under 10:1, and in glare there should not be an occurrence factor from a reflector outside of the classroom. And the factors of unnatural lighting are illumination, brightness, and glare. In the standard on each factor, illumination should be 750 lux or more, brightness ratio should be under 3 to 1, and glare should not occur. And Optimal reflection rate(%) of Colors and Facilities of Classroom which influences lighting environment should be considered. 3) In indoor air environment factors, thermal factors are divided into (1) room temperature, (2) relative humidity, (3) room air movement, (4) radiation heat, and harmful gases (5) CO, (6) $CO_2$ that are proceeded from using the heating fuel such as oval briquettes, firewood, charcoal being used in most of the classroom, and finally (7) dust. In the standard on each factor, the next are necessary; room temperature: $16^{\circ}C{\sim}26^{\circ}C$(summer : $E.T18.9{\sim}23.8^{\circ}C$, winter: $E.T16.7{\sim}21.7^{\circ}C$), relative humidity: $30{\sim}80%$, room air movement: under 0.5m/sec, radiation heat: under $5^{\circ}C$ gap between dry-bulb temperature and wet-bulb temperature, below 1000 ppm of ca and below 10ppm of $CO_2$, dust: below 0.10 $mg/m^3$ of Volume of dust in indoor air, and ventilation standard($CO_2$) for purification of indoor air : once/6 min.(about 7 times/40 min.) in an airtight classroom. 4) In the standard on noise environment, noise level should be under 40 dB(A) and the noise measuring way and the countermeasures against it should be considered. 5) In the standard on odor environment, odor level under Physical Method should be under 2 degrees, and the inspecting way and the countermeasures against it should be considered.

• Journal of the Korean Ceramic Society
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• v.34 no.2
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• pp.145-156
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• 1997

ZrO2 phase transformations depending on the type and amount of dopants and the sintering temperatures were studied for the 2 components (CaO-, Y2O3-, MgO-ZrO2) and the 3 components(MgO-ZrO2-Al2O3)ZrO2 powder by X-ray diffraction and Raman spectroscopy. In the CaO- and Y2O3-ZrO2 systems, as the CaO and Y2O3 contents increased to 6~15mol% and 3~15mol% respectively, we were not able to identify between tetragonal and cubic in the X-ray diffraction patterns. On the other hand, all Raman modes shifted to lower wavenumbers, decreasing in intensity and the number of bands, markedly. These phenomena were caused by tetragonallongrightarrowcubic phase transformation and interpreted by the breakdown of the wave vector selection rule(k=0) and the structural disorder associated with the formation of oxygen sublattice which was caused by the substitution between Zr4+ ion and Ca2+ or Y3+ ion in ZrO2 matrix. The monoclinic to cubic phase transformation occurred in 10mol% MgO-ZrO2 system. As the Al2O3 content increased from 0 to 20mol% in the MgO-ZrO2-Al2O3 systems, cubic phase transformed to monoclinic phase, this is because the MgO didn't play a role in a stabilizer because of the formation of the spinel(MgAl2O4) by the reaction between MgO and Al2O3, Also, the ZrO2 phase transformation was explained by the change of it's lattice parameters depending on the type and amount of dopants. Namely, as the amount of dopant increased to 10~13mol%, the axial ra-tio c/a came close to unity with increasing the lattice parameter a and decreasing the lattice parameter c. At that time, the tetragonallongrightarrowcubic phase transformation occurred.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.3
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• pp.255-264
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• 2012

Purpose: In this study, the effect of lens fitting status on the contact area between spherical/aspherical RGP lens and the cornea having different astigmatic degree and corneal type was investigated for guiding the proper selection of RGP lens. Methods: Spherical and aspherical RGP lenses were applied on ninety eyes $(25.12{\pm}3.52years)$ having with-the-rule astigmatism by different fitting status. Then, their central, mid-peripheral and peripheral areas of fluorescein pattern were calculated and compared for the quantitative evaluation of the contact area between spherical/aspherical RGP lens. Results: The central and peripheral areas with the alignment fitting was significant different based on lens design. However, the central area didn't show any significant difference by lens design and corneal type when fitted in steep or flat. When analyzed by the corneal shape, both lenses with alignment and flat fitting had significant difference in central and peripheral areas. However, the central, mid-peripheral and peripheral areas with steep fitting didn't show the difference by corneal types. When analyzed by the astigmatic degree, the central and peripheral areas with alignment fitting changed proportionally to the increase of corneal astigmatism regardless of corneal shape. With steep and flat fitting, however, the central, mid-peripheral and/or peripheral areas in round- and symmetric bowtie-typed corneas showed the conflicting result when compared to those of alignment fitting when analyzed by the astigmatic degree. Conclusions: In this study, it was confirmed that the contact areas of cornea and RGP lens fitted steep and flat status were largely affected by the corneal type and corneal astigmatism rather than RGP lens fitted in alignment status. Also, this result commonly occurred in both spherical and aspherical RGP lenses.

• Korean Journal of Digital Imaging in Medicine
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• v.5 no.1
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• pp.64-77
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• 2002

DR has had an important fact not only in the department of radiology but also in productivity or work efficiency of a whole hospital. The environment of DR has more various parameter than CR, so it is able to supply high quality of medical services. The current environment of radiology department in each hospital has been changed from Film-Screen system to DR through Full-PACS. This hospital which uses Full-PACS became to study the proper condition of CR and DDR and how the image quality of them is expressed among general photographing systems in the DR environment. From this experiment, the image quality of DDR is better than CR under the same exposure condition. And in the DDR system, the score of image which uses AEC is a little higher than the score which doesn't use it. Especially it can be known that the function of AEC of DDR is useful to improve the image quality in the part of skull and chest. (The function of AEC : It is the tool that detects the ionized current of x-ray which goes through objects with using the ion chamber which is in the detector. Also it controls the examination of X-ray when the proper density is reached.) Because the proper degree of density can be represented by this system, the photographing can be taken much easily without consideration of the exposure condition with the thickness of various objects. From the result of this experiment, it can be known that the selection of proper exposure condition plays an important rule to gain good Image Quality. More researches will be necessary about DDR system which has potential ability in the future.

• Journal of the Korea Computer Graphics Society
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• v.6 no.4
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• pp.1-7
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• 2000

Traditionally, three dimension model s have been used for building virtual worlds, and a data structure called the "scene graph" is often employed to organize these 3D objects in the virtual space. On the other hand, image-based rendering has recently been suggested as a probable alternative VR platform for its photo-realism, however, due to limited interactivity. it has only been used for simple navigation systems. To combine the merits of these two approaches to object/scene representations, this paper proposes for a scene graph structure in which both 3D models and various image-based scenes/objects can be defined. traversed, and rendered together. In fact, as suggested by Shade et al. [1]. these different representations can be used as different LOD's for a given object. For in stance, an object might be rendered using a 3D model at close range, a billboard at an intermediate range. and as part of an environment map at far range. The ultimate objective of this mixed platform is to breath more interactivity into the image based rendered VE's by employing 3D models as well. There are several technical challenges in devising such a platform : designing scene graph nodes for various types of image based techniques, establishing criteria for LOD/representation selection. handling their transition s. implementing appropriate interaction schemes. and correctly rendering the overall scene. Currently, we have extended the scene graph structure of the Sense8's WorldToolKit. to accommodate new node types for environment maps. billboards, moving textures and sprites, "Tour-into-the-Picture" structure, and view interpolated objects. As for choosing the right LOD level, the usual viewing distance and image space criteria are used, however, the switching between the image and 3D model occurs at a distance from the user where the user starts to perceive the object's internal depth. Also. during interaction, regardless of the viewing distance. a 3D representation would be used, if it exists. Finally. we carried out experiments to verify the theoretical derivation of the switching rule and obtained positive results.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.