• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Korean Home Economics Education Association
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• v.24 no.2
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• pp.117-134
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• 2012

The purpose of this study was to identify the stage of concern, the level of use, and the innovation configuration of Home Economics teachers regarding creativity and personality education in Home Economics(HE) classes. The survey questionnaires were sent through mails and e-mails to middle-school HE teachers in the whole country selected by systematic sampling and convenience sampling. Questionnaires of the stages of concern and the levels of use developed by Hall(1987) were used in this study. 187 data were used for the final analysis by using SPSS/window(12.0) program. The results of the study were as following: First, for the stage of concerns of HE teachers on creativity and personality education, the information stage of concerns(85.51) was the one with the highest response rate and the next high in the following order: the management stage of concerns(81.88), the awareness stage of concerns(82.15), the refocusing stage of concerns(68.80), the collaboration stage of concerns(61.97), and the consequence stage of concerns(59.76). Second, the levels of use of HE teachers on creativity and personality education was highest with the mechanical levels(level 3; 21.4%) and the next high in the following order: the orientation levels of use(level 1; 20.9%), the refinement levels(level 5; 17.1%), the non-use levels(level 0; 15.0%), the preparation levels(level 2; 10.2%), the integration levels(level 6; 5.9%), the renewal levels(level 7; 4.8%), the routine levels(level 4; 4.8%). Third, for the innovation configuration of HE teachers on creativity and personality education, more than half of the HE teachers(56.1%) mainly focused on personality education in their HE classes; 31.0% of the HE teachers performed both creativity and personality education; a small number of teachers(6.4%) focused on creativity education; the same number of teachers(6.4%) responded that they do not focus on neither of the two. Examining the level and type of performance HE teachers applied, the average score on the performance of creativity and personality education was 3.76 out of 5.00 and the mean of creativity component was 3.59 and of personality component was 3.94, higher than standard. For the creativity education, openness/sensitivity(3.97) education was performed most and the next most in the following order: problem-solving skill(3.79), curiosity/interest(3.73), critical thinking(3.63), problem-finding skill(3.61), originality(3.57), analogy(3.47), fluency/adaptability(3.46), precision(3.46), imagination(3.37), and focus/sympathy(3.37). For the personality education, the following components were performed in order from most to least: power of execution(4.07), cooperation/consideration/just(4.06), self-management skill(4.04), civic consciousness(4.04), career development ability(4.03), environment adaptability(3.95), responsibility/ownership(3.94), decision making(3.89), trust/honesty/promise(3.88), autonomy(3.86), and global competency(3.55). Regarding what makes performing creativity and personality education difficult, most HE teachers(64.71%) chose the lack of instructional materials and 40.11% of participants chose the lack of seminar and workshop opportunity. 38.5% chose the difficulty of developing an evaluation criteria or an evaluation tool while 25.67% responded that they do not know any means of performing creativity and personality education. Regarding the better way to support for creativity and personality education, the HE teachers chose in order from most to least: 'expansion of hands-on activities for students related to education on creativity and personality'(4.34), 'development of HE classroom culture putting emphasis on creativity and personality'(4.29), 'a proper curriculum on creativity and personality education that goes along with students' developmental stages'(4.27), 'securing enough human resource and number of professors who will conduct creativity and personality education'(4.21), 'establishment of the concept and value of the education on creativity and personality'(4.09), and 'educational promotion on creativity and personality education supported by local communities and companies'(3.94).

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Journal of Korean Society of Forest Science
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• v.22 no.1
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• pp.19-48
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• 1974

Land was originally communized by a community in the primitive society of Korea, and in the age of the ancient society SAM KUK-SILLA, KOKURYOE and PAEK JE-it was distributed under the principle of land-nationalization. But by the occupation of the lands which were permitted to transmit from generation to generation as Royal Grant Lands and newly cleared lands, the private occupation had already begun to be formed. Thus the private ownership of land originated by chiefs of the tribes had a trend to be gradually pervaded to the communal members. After the, SILLA Kingdom unified SAM KUK in 668 A.D., JEONG JEON System and KWAN RYO JEON System, which were the distribution systems of farmlands originated from the TANG Dynasty in China, were enforced to established the basis of an absolute monarchy. Even in this age the forest area was jointly controlled and commonly used by village communities because of the abundance of area and stocked volume, and the private ownership of the forest land was prohibited by law under the influence of the TANG Dynasty system. Toward the end of the SILLA Dynasty, however, as its centralism become weak, the tendency of the private occupancy of farmland by influential persons was expanded, and at the same time the occupancy of the forest land by the aristocrats and Buddhist temples began to come out. In the ensuing KORYO Dynasty (519 to 1391 A.D.) JEON SI KWA System under the principle of land-nationalization was strengthened and the privilege of tax collection was transferred to the bureaucrats and the aristocrats as a means of material compensation for them. Taking this opportunity the influential persons began to expand their lands for the tax collection on a large scale. Therefore, about in the middle of 11th century the farmlands and the forest lands were annexed not only around the vicinity of the capital but also in the border area by influential persons. Toward the end of the KORYO Dynasty the royal families, the bureaucrats and the local lords all possessed manors and occupied the forest lands on a large scale as a part of their farmlands. In the KORYO Dynasty, where national economic foundation was based upon the lands, the disorder of the land system threatened the fall of the Dynasty and so the land reform carried out by General YI SEONG-GYE had led to the creation of ensuing YI Dynasty. All systems of the YI Dynasty were substantially adopted from those of the KORYO Dynasty and thereby KWA JEON System was enforced under the principle of land-nationalization, while the occupancy or the forest land was strictly prohibited, except the national or royal uses, by the forbidden item in KYEONG JE YUK JEON SOK JEON, one of codes provided by the successive kings in the YI Dynasty. Thus the basis of the forest land system through the YI Dynasty had been established, while the private forest area possessed by influential persons since the previous KORYO Dynasty was preserved continuously under the influence of their authorities. Therefore, this principle of the prohibition was nothing but a legal fiction for the security of sovereign powers. Consequently the private occupancy of the forest area was gradually enlarged and finally toward the end of YI Dynasty the privately possessed forest lands were to be officially authorized. The forest administration systems in the YI Dynasty are summarized as follows: a) KEUM SAN and BONG SAN. Under the principle of land-nationalization by a powerful centralism KWA JEON System was established at the beginning of the YI Dynasty and its government expropriated all the forests and prohibited strictly the private occupation. In order to maintain the dignity of the royal capital, the forests surounding capital areas were instituted as KEUM SAN (the reserved forests) and the well-stocked natural forest lands were chosen throughout the nation by the government as BONG SAN(national forests for timber production), where the government nominated SAN JIK(forest rangers) and gave them duties to protect and afforest the forests. This forest reservation system exacted statute labors from the people of mountainious districts and yet their commons of the forest were restricted rigidly. This consequently aroused their strong aversion against such forest reservation, therefore those forest lands were radically spoiled by them. To settle this difficult problem successive kings emphasized the preservation of the forests repeatedly, and in KYEONG KUK DAI JOEN, the written constitution of the YI Dynasty, a regulation for the forest preservation was provided but the desired results could not be obtained. Subsequently the split of bureaucrats with incessant feuds among politicians and scholars weakened the centralism and moreover, the foreign invasions since 1592 made the national land devasted and the rural communities impoverished. It happned that many wandering peasants from rural areas moved into the deep forest lands, where they cultivated burnt fields recklessly in the reserved forest resulting in the severe damage of the national forests. And it was inevitable for the government to increase the number of BONG SAN in order to solve the problem of the timber shortage. The increase of its number accelerated illegal and reckless cutting inevitably by the people living mountainuos districts and so the government issued excessive laws and ordinances to reserve the forests. In the middle of the 18th century the severe feuds among the politicians being brought under control, the excessive laws and ordinances were put in good order and the political situation became temporarily stabilized. But in spite of those endeavors evil habitudes of forest devastation, which had been inveterate since the KORYO Dynasty, continued to become greater in degree. After the conclusion of "the Treaty of KANG WHA with Japan" in 1876 western administration system began to be adopted, and thereafter through the promulgation of the Forest Law in 1908 the Imperial Forests were separated from the National Forests and the modern forest ownership system was fixed. b) KANG MU JANG. After the reorganization of the military system, attaching importance to the Royal Guard Corps, the founder of the YI Dynasty, TAI JO (1392 to 1398 A.D.) instituted the royal preserves-KANG MU JANG-to attain the purposes for military training and royal hunting, prohibiting strictly private hunting, felling and clearing by the rural inhabitants. Moreover, the tyrant, YEON SAN (1495 to 1506 A.D.), expanded widely the preserves at random and strengthened its prohibition, so KANG MU JANG had become the focus of the public antipathy. Since the invasion of Japanese in 1592, however, the innovation of military training methods had to be made because of the changes of arms and tactics, and the royal preserves were laid aside consequently and finally they had become the private forests of influential persons since 17th century. c) Forests for official use. All the forests for official use occupied by government officies since the KORYO Dynasty were expropriated by the YI Dynasty in 1392, and afterwards the forests were allotted on a fixed standard area to the government officies in need of firewoods, and as the forest resources became exhausted due to the depredated forest yield, each office gradually enlarged the allotted area. In the 17th century the national land had been almost devastated by the Japanese invasion and therefore each office was in the difficulty with severe deficit in revenue, thereafter waste lands and forest lands were allotted to government offices inorder to promote the land clearing and the increase in the collections of taxes. And an abuse of wide occupation of the forests by them was derived and there appeared a cause of disorder in the forest land system. So a provision prohibiting to allot the forests newly official use was enacted in 1672, nevertheless the government offices were trying to enlarge their occupied area by encroaching the boundary and this abuse continued up to the end of the YI Dynasty. d) Private forests. The government, at the bigninning of the YI Dynasty, expropriated the forests all over the country under the principle of prohibition of private occupancy of forest lands except for the national uses, while it could not expropriate completely all of the forest lands privately occupied and inherited successively by bureaucrats, and even local governors could not control them because of their strong influences. Accordingly the King, TAI JONG (1401 to 1418 A.D.), legislated the prohibition of private forest occupancy in his code, KYEONG JE YUK JEON (1413), and furthermore he repeatedly emphasized to observe the law. But The private occupancy of forest lands was not yet ceased up at the age of the King, SE JO (1455 to 1468 A.D.), so he prescribed the provision in KYEONG KUK DAI JEON (1474), an immutable law as a written constitution in the YI Dynasty: "Anyone who privately occupy the forest land shall be inflicted 80 floggings" and he prohibited the private possession of forest area even by princes and princesses. But, it seemed to be almost impossible for only one provsion in a code to obstruct the historical growing tendecy of private forest occupancy, for example, the King, SEONG JONG (1470 to 1494 A.D.), himself granted the forests to his royal families in defiance of the prohibition and thereafter such precedents were successively expanded, and besides, taking advantage of these facts, the influential persons openly acquired their private forest lands. After tyrannical rule of the King, YEON SAN (1945 to 1506 A.D.), the political disorder due to the splits to bureaucrats with successional feuds and the usurpations of thrones accelerated the private forest occupancy in all parts of the country, thus the forbidden clause on the private forest occupancy in the law had become merely a legal fiction since the establishment of the Dynasty. As above mentioned, after the invasion of Japanese in 1592, the courts of princes (KUNG BANGG) fell into the financial difficulties, and successive kings transferred the right of tax collection from fisherys and saltfarms to each KUNG BANG and at the same time they allotted the forest areas in attempt to promote the clearing. Availing themselves of this opportunity, royal families and bureaucrats intended to occupy the forests on large scale. Besides a privilege of free selection of grave yard, which had been conventionalized from the era of the KORYO Dynasty, created an abuse of occuping too wide area for grave yards in any forest at their random, so the King, TAI JONG, restricted the area of grave yard and homestead of each family. Under the policy of suppresion of Buddhism in the YI Dynasty a privilege of taxexemption for Buddhist temples was deprived and temple forests had to follow the same course as private forests did. In the middle of 18th century the King, YEONG JO (1725 to 1776 A.D.), took an impartial policy for political parties and promoted the spirit of observing laws by putting royal orders and regulations in good order excessively issued before, thus the confused political situation was saved, meanwhile the government officially permittd the private forest ownership which substantially had already been permitted tacitly and at the same time the private afforestation areas around the grave yards was authorized as private forests at least within YONG HO (a boundary of grave yard). Consequently by the enforcement of above mentioned policies the forbidden clause of private forest ownership which had been a basic principle of forest system in the YI Dynasty entireely remained as only a historical document. Under the rule of the King, SUN JO (1801 to 1834 A.D.), the political situation again got into confusion and as the result of the exploitation from farmers by bureaucrats, the extremely impoverished rural communities created successively wandering peasants who cleared burnt fields and deforested recklessly. In this way the devastation of forests come to the peak regardless of being private forests or national forests, moreover, the influential persons extorted private forests or reserved forests and their expansion of grave yards became also excessive. In 1894 a regulation was issued that the extorted private forests shall be returned to the initial propriators and besides taking wide area of the grave yards was prohibited. And after a reform of the administrative structure following western style, a modern forest possession system was prepared in 1908 by the forest law including a regulation of the return system of forest land ownership. At this point a forbidden clause of private occupancy of forest land got abolished which had been kept even in fictitious state since the foundation of the YI Dynasty. e) Common forests. As above mentioned, the forest system in the YI Dynasty was on the ground of public ownership principle but there was a high restriction to the forest profits of farmers according to the progressive private possession of forest area. And the farmers realized the necessity of possessing common forest. They organized village associations, SONGE or KEUM SONGE, to take the ownerless forests remained around the village as the common forest in opposition to influential persons and on the other hand, they prepared the self-punishment system for the common management of their forests. They made a contribution to the forest protection by preserving the common forests in the late YI Dynasty. It is generally known that the absolute monarchy expr opriates the widespread common forests all over the country in the process of chainging from thefeudal society to the capitalistic one. At this turning point in Korea, Japanese colonialists made public that the ratio of national and private forest lands was 8 to 2 in the late YI Dynasty, but this was merely a distorted statistics with the intention of rationalizing of their dispossession of forests from Korean owners, and they took advantage of dead forbidden clause on the private occupancy of forests for their colonization. They were pretending as if all forests had been in ownerless state, but, in truth, almost all the forest lands in the late YI Dynasty except national forests were in the state of private ownership or private occupancy regardless of their lawfulness.