• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3159-3174
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• 1997

This paper reports a research to develop a methodology and a tool for understanding of very large and complex real-time software. The methodology and the tool mostly developed by the author are called the Architecture-based Real-time Software Understanding (ARSU) and the Software Re/reverse-engineering Environment (SRE) respectively. Due to size and complexity, it is commonly very hard to understand the software during reengineering process. However the research facilitates scalable re/reverse-engineering of such real-time software based on the architecture of the software in three-dimensional perspectives: structural, functional, and behavioral views. Firstly, the structural view reveals the overall architecture, specification (outline), and the algorithm (detail) views of the software, based on hierarchically organized parent-chi1d relationship. The basic building block of the architecture is a software Unit (SWU), generated by user-defined criteria. The architecture facilitates navigation of the software in top-down or bottom-up way. It captures the specification and algorithm views at different levels of abstraction. It also shows the functional and the behavioral information at these levels. Secondly, the functional view includes graphs of data/control flow, input/output, definition/use, variable/reference, etc. Each feature of the view contains different kind of functionality of the software. Thirdly, the behavioral view includes state diagrams, interleaved event lists, etc. This view shows the dynamic properties or the software at runtime. Beside these views, there are a number of other documents: capabilities, interfaces, comments, code, etc. One of the most powerful characteristics of this approach is the capability of abstracting and exploding these dimensional information in the architecture through navigation. These capabilities establish the foundation for scalable and modular understanding of the software. This approach allows engineers to extract reusable components from the software during reengineering process.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.1
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• pp.3-32
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• 2014

Safety Management System is the aviation industry policy for while operating the aircraft, to ensure the safety crew, aircraft and passengers. For operating a safe aircraft, in order to establish the international technical standards, the International Civil Aviation Organization has established the Annex 19 of the Convention on International Civil Aviation. As a result, member country was supposed to be in accordance with the policy of the International Civil Aviation Organization, to accept the international standard of domestic air law. The South Korean government announced that it would promote active safety management strategy in primary aviation policy master plan of 2012. And, by integrating and state safety programmes(ssp) and safety management system(sms) for the safe management of Annex 19 is to enforce the policy on aviation safety standards. State safety programmes(ssp) is a system of activities for the aim of strengthening the safety and integrated management of the activities of government. State safety programmes(ssp) is important on the basis of the data of the risk information. Collecting aviation hazard information is necessary for efficient operation of the state safety programmes(ssp) Korean government must implement the strategy required to comply with aviation methods and standards of the International Civil Aviation Organization. Airlines, must strive to safety features for safety culture construction and improvement of safety management is realized. It is necessary to make regulations on the basis of the aviation practice, for aviation safety regulatory requirements, aviation safety should reflect the opinion of the aviation industry.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.127-139
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• 2013

With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

• Journal of Korean Home Economics Education Association
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• v.25 no.1
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• pp.95-118
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• 2013

The purpose of this study was to analyze the contents of housing related to characters, objectives, and contents of FCS curricular from the 1st to 2009 revised curriculum of secondary school. The data were downloaded from the NCIC homepage(http://www.ncic.re.kr/2012. 04. 08) from the 1st(1955. 08) to 2009 revised curriculum(2012. 03) of secondary school. After examining the characters and objectives of each curriculum, contents of housing was analyzed by units and context elements of middle and high school separately. The titles of the subject, the objectives, the instructions, the leaning spheres, weekly hours, grade and gender of candidates, the emphasis of the instruction, etc. have been changed through the curriculum revision. The 6th curriculum was the main period to open to both genders, the $7^{th}$ was the period to combine with technology, the 2007 version was to change the structure of contents of home economics, and the 2009 version switched technology home economics from mandatory to optional in high school. The character of the courses was presented at the 1st curriculum, but it was left out from the $2^{nd}$ to $5^{th}$ curriculum. From the $6^{th}$ curriculum, the characters were separately given to middle and high school. The character of housing area started to appear only in high school home economics from the $7^{th}$ curriculum. The course objectives were described in all curriculum of both middle and high school. This applies to housing area as well. The course objectives have been modified in order to reflect value changes due to social issues. During each curriculum, contents of housing continued to change in context, course load, and candidates. Reflection of housing trends and social needs were the main causes of the change. 2009 version emphasizes on eco-life and sense of community.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.27-44
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• 1999

Digital maps produced in Korea are various in scale and include a lot of geographic and attribute data. In this study, it is argued that, to reduce the production cost and the difficulties for renewal, it is necessary to establish the already nationally drawn 1:5,000 scale digital maps as the base maps and simplify them as much as the TIGER files in the U.S. The comprehensive data included in the digital maps in Korea are mostly land use information, which are supposed to be established separately from the digital maps. The land use information system could be maintained and updated cheaply and frequently at the local government level. In response to common needs, the land use information could be imported to GIS and used for analyses. As technologies and societies changes, the Census questions and methodologies should be changed for better uses. Along with GIS, the Census would be developed and processed more reliably and efficiently. Also, it is recommended for Korean government to develop the Census Tract and Block Group system. Current Eup, Myon, Dong as basic units for Census information may not be useful or effective for micro level urban analyses and public service planning activities because of their large population and land areas. It is recommended that optimum population of a Census Tract be 5,000 and a Block Groups 1,500, and one Census Tract includes 1~9 Block Groups. It is recommend that Census Tract and Block Group boundary lines be decided flexibly in light of population, physical features, socio-economic attributes, and tradition. For urban analyses using GIS, socio-economic census data, city government's information such as parcel data and building permit data, survey data, and satellite image data could also be used. The existence of Census Tracts and Block Groups as well as GIS could help for the data and methods to be useful for urban analyses and public service provisions.

• Journal of The Korean Association of Information Education
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• v.5 no.1
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• pp.33-45
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• 2001

In order to adapt ourselves to the Informationalization Society of twenty-first century, it is required to have ability to find quickly the necessary information and solve the problem of our own. In the field of school, it should be educated to develop learner's ability that can cope with the Informationalization Society. When a learner can study in such direction, he or she will be able to plan the learning of his own as the subject of education, and develop his ability to solve the problem by collecting and examining various information. It is self-leading learning that can make education like this possible. Through computer, especially Web site, self-directed learning can develop can develop the individuality and creativity of learners. They can collect and utilize autonomously information and knowledge. To do such an education, the program that can work out self-directed learning is needed. Therefore the program I want to develop is to reconstruct the 'figure' part of mathematics in elementary school into five steps by utilizing Web site. In the first step is to learn the concept of various shape. This step enable learners to know what figure is and how it can be utilized in our real life. The second step of dot, line and angle makes it possible that learners can consolidate the foundation of the study about figure and recognize the relation between angle and figure. In the third step of plane figure, we can study how to calculate the relation of plane figures and the area of figure with various shapes by cutting and adding them. The fourth step is about congruence and symmetry. Learners can learn to know the figure in congruence, reduction and enlargement and how it is used in our real life. In the fifth step of solid figure, we can learn the relation among the plane figure, solid figure, the body of revolution, corn and pyramid etc. controling the speed of learning on the basis of his ability. In the process of the program, it is also possible to develop learner's ability of self-leading learning by solving the problem by himself. Because this program is progressed on the Web site, it is possible to learn anytime and anywhere. In addition to it, a learner can learn beyond the grade as well as do the perfect learning by controling the pace of learning on the basis of his ability. In the process of the program, it is also possible to develop learner's ability of self-leading learning by solving the problem by himself.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.28-28
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• 2011

국내의 건축물에 관한 통계정보는 국토해양부에 의해서 공표된 통계연보로서 2002년부터 매년마다 제공되고 있다.(국토해양통계누리, https : //stat.mltm.go.kr/potal/stat/yearReport.do) 건축물의 통계연보는 과거부터 2002년까지 매 3년마다 공표된 것으로 알려지고 있다. 이 통계연보에는 건축물 현황과 건축허가착공 통계가 수록되어 있다. 건축물 현황에는 2009년 말을 기준으로 기존 건축물이 전체 6,618,131동으로서 용도별, 층수와 연면적별 그리고 소유구분별 등의 구분에 따라 건축물의 동수에 관한 통계자료가 포함돼 있다. 건축허가 및 착공통계에는 용도별과 구조재료별의 분류에 따라 건축물의 동수에 관한 자료가 신축, 증축 개축 이전 대수선, 용도변경 등으로 분류되어 수록돼 있다. 한편 국내에서 건축물에 대한 내진설계기준이 1988년에 제정됨에 따라 법제화되었다. 이때 내진설계의 의무 대상건축물은 6층 이상 또는 연면적 1만$m^2$이상인 건축물로 규정되었다. 그 이후 내진설계 대상 건축물이 1996년부터 아파트는 5층 이상으로, 판매시설은 연면적 5천$m^2$이상으로 확대되었고, 2000년부터 숙박시설 오피스텔 및 기숙사는 5층 이상으로 확대되었으며, 2005년부터 내진설계 의무화 대상이 3층 이상 또는 1천$m^2$이상으로 확대되었고, 2009년부터 3층 이상 건축물의 구조안전의 확인을 위한 세부절차를 규정하여 내진설계의 실효성을 확보하고 있다. 이와 같이 내진설계의 대상 건축물이 내진설계기준을 제정한 이후 현재까지 시대의 흐름에 따라 6층 이상에서 5층 이상으로 다시 3층 이상으로 계속 확대되어왔다. 이런 환경에서 현재 시점에서 사용 중인 기존 건축물 중에 내진설계가 적용되지 아니한 건축물은 1988년 3월 1일 이전에 건축허가 된 건축물과 그 이후에 건축허가 된 3층 내지 5층 이하인 저층 건축물의 두 가지로 구분할 수 있다. 이들의 내진설계가 미적용 된 건축물에 대해서는 원칙적으로 내진보강 대책 수립 및 추진이 필요한 실정이다. 국내에서는 현재 지진재해대책법에 따라 지진재해로부터 국민의 생명과 재산을 보호하기 위하여 기존 시설물에 대한 내진대책을 추진하는 정책이 시행되고 있다. 앞으로는 이 정책의 일환으로 기존 건축물의 내진성능 확보를 위한 내진보강 대책이 구체적으로 추진될 전망이다. 이와 같이 기존 건축물에 대한 내진보강 대책을 수립하는 데는 무엇보다 그 대상 건축물의 수와 구조형식에 관한 정보가 필요하다. 이는 내진보강의 방법과 소요비용이 건축물의 층수 및 구조형식별 동수에 따라 크게 달라지기 때문이다. 이런 관점에서 살펴볼 때 내진대책의 수립에 필수인 기존 저층 건축물의 층수 및 구조형식별 동수에 관한 통계자료를 현재 건축물의 현황통계에서 손쉽게 찾아 볼 수 있으면 좋겠는데 현실은 그렇지 못한 실정이다. 현재 건축물의 현황통계에는 저층 건축물에 해당하는 층수에 관한 구분이 연대에 따라 다르고 구체적인 층수를 구분하기 어렵게 불분명한 항목으로 구성된 것과 구조형식별 분류항목이 없는 형편이다. 반면에 건축허가 및 착공통계자료에는 구조재료별 건축물 동수와 연면적에 관한 자료가 수록되어있고, 건축물 층수에 따라 분류된 통계자료는 없다. 이 연구에서는, 기존 건축물에 대한 내진보강 대책을 수립하는데 필요한 저층 건축물의 층수 및 구조재료별 동수 등에 관한 구체적인 정보를 파악하기 위하여, 건축물 통계연보에 수록된 건축물 현황통계자료에서 불명확하거나 결여된 정보를 건축허가 및 착공 통계자료로부터 얻은 정보로 보완과 보충하여 제시하고 있다. 따라서 이 연구는 기존 건축물의 내진보강 대책 수립에 필요한 5층 이하의 저층 건축물에 관한 층수별 및 구조형식별 동수에 관한 연도별 통계자료를 추정하여 제안하는데 그 목적이 있다.