• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.265-274
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• 2017

This paper examines the problems of big data analysis education and suggests ways to solve them. Big data is a trend that the characteristic of big data is evolving from V3 to V5. For this reason, big data analysis education must take V5 into account. Because increased uncertainty can increase the risk of data analysis, internal and external structured/semi-structured data as well as disturbance factors should be analyzed to improve the reliability of the data. And when using opinion mining, error that is easy to perceive is variability and veracity. The veracity of the data can be increased when data analysis is performed against uncertain situations created by various variables and options. It is the node analysis of the textom(텍스톰) and NodeXL that students and researchers mainly use in the analysis of the association network. Social network analysis should be able to get meaningful results and predict future by analyzing the current situation based on dark data gained.

• The Mathematical Education
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• v.37 no.1
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• pp.87-99
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• 1998

Mathematics education is very important in future because mathematics is the basis of every study, for example, natural and social science, etc. Our nation wide curriculum has been revised six times since 1948. In 1992, the sixth revision was enforced and we are using the revised textbook now. This study aims at helping of continuous investigation for educational curriculum and textbook, and aims at efficient teaching by preventing unnecessary repetition and excessive gap in real field by analyzing the articulation of Analytics part in school textbook from elementary to high school. This thesis consists of the followings. 1.Investigation of the principles and natures of articulation along with curriculum course and notice the articulation based on the analysing tools. 2.Importance of learning functions. 3.To get the propriety, formation of 8 judging group and classification of content materials in function chapters by the judges based on the analyzing tools. 4.Analysis of presentation method and terminologies in the first concepts, suggestion teaching method to reduce gap and help of understanding on first concepts in the study of function. As a result 'development' consists of 55.8% of the total and it is higher than 'duplication' and 'gap'. To be specific in periods, between elementary school and middle school 'development' takes 64.5% and this shows an acceptable articulation in the period. While 39.4% of 'gap' in articulation between middle school and high school looks high compared with 'gap' between the previous periods. The item suggested with the 'gap' is the 'definition of function', 'value of function', 'parallel translation', 'exponential and logarithmic function'. It is observed that these materials is suddenly appeared in high school.

• Journal of Korea Game Society
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• v.18 no.2
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• pp.27-36
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• 2018

In this paper, we propose a win-win network operating platform for mobile games. The characteristics of the service structure suggested is to form a marketing network that can influence the mobile game market by linking with the mobile game industry, and the excellent game content of the game developer in the industrial complex may not disappear. We also would like to propose a network operating platform that would help it enter the market area steadily. The proposed platform technology is used to distribute rapidly through a win-win network between game companies and publishers. When new games are commercialized, they can support continuous target marketing through various data indicators and analytics by the developed platform. In particular, G-Cross marketing strategy is considered to be a low-cost, high-efficiency marketing method in that it can provide users with information about new games by utilizing the given game infrastructure and utilize the user group possessed by each game company.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.178-183
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• 2008

The goal of this study is finding flow-map in conversation what is going on user and embodied conversational agent by analysing that conversation. Specifically, this study not only find elements of conversation, but also draw out patterns of conversation can be exist for dialogue ability between user and Embodied conversational agent. To do this, we collect data through in-depth one to one interview, and then we analysis collected data to try to find out element of user-agent conversation based on qualitative research refer to the theory of conversation analytics and type of conversation. As a result, six flow map is deducted Especially, the irregular conversation is hard to find in human-human conversation, and the frequency is the most in data. In addition, when elements of interruption came out, be hostile to partner or correct the press conversation. This study can have positive effect to embodied conversation agent developer, user and service offerer because this study find the type of conversation through analysis that between embodied conversational agent and user.

• The Journal of Bigdata
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• v.1 no.2
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• pp.9-19
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• 2016

Since ICT convergence became a major issue, German government has carried forward a policy 'Industry 4.0' that triggered ICT convergence with manufacturing. Now this trend gets into our stride. From this facts, we can expect great leap up to quality perfection in low cost. Recently Korean government also enforces policy with 'Manufacturing 3.0' for upgrading Korean manufacturing industry with being accelerated by many related technologies. We, in the paper, developed a custom-made operational big data analysis platform for the implementation of operational intelligence to improve industry capability. Our platform is designed based on spring framework and web. In addition, HDFS and spark architectures helps our system analyze massive data on the field with streamed data processed by process mining algorithm. Extracted knowledge from data will support enhancement of manufacturing performance.

• Korean Journal of Clinical Pharmacy
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• v.27 no.4
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• pp.221-227
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• 2017

Background: As personalized healthcare industry has attracted much attention, big data analysis of healthcare data is essential. Lots of healthcare data such as product labeling, biomedical literature and social media data are unstructured, extracting meaningful information from the unstructured text data are becoming important. In particular, text mining for adverse drug reactions (ADRs) reports is able to provide signal information to predict and detect adverse drug reactions. There has been no study on text analysis of expert opinion on Korea Adverse Event Reporting System (KAERS) databases in Korea. Methods: Expert opinion text of KAERS database provided by Korea Institute of Drug Safety & Risk Management (KIDS-KD) are analyzed. To understand the whole text, word frequency analysis are performed, and to look for important keywords from the text TF-IDF weight analysis are performed. Also, related keywords with the important keywords are presented by calculating correlation coefficient. Results: Among total 90,522 reports, 120 insulin ADR report and 858 tramadol ADR report were analyzed. The ADRs such as dizziness, headache, vomiting, dyspepsia, and shock were ranked in order in the insulin data, while the ADR symptoms such as vomiting, 어지러움, dizziness, dyspepsia and constipation were ranked in order in the tramadol data as the most frequently used keywords. Conclusion: Using text mining of the expert opinion in KIDS-KD, frequently mentioned ADRs and medications are easily recovered. Text mining in ADRs research is able to play an important role in detecting signal information and prediction of ADRs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2308-2314
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• 2006

Internet Technology allowed general commerce to have proceeded actively, and now it is sharply evolving into Mobile Commerce. Mobile Commerce came into an inheritance of the Electronic Commerce, thought the feature to be different form is various as well. Many researches that analyzed the feature of Electronic Commerce were carried out but those were processed according to its location and field only. This study extracted and analyzed the factor that considered the several positions for Mobile Commerce so that it can reflect diverse the demands from those related to Mobile Commerce. It sought the new characteristic which is different from the Electronic Commerce, and took account of the successful factor for Mobile Commerce which includes the position in a user, a developer and an operator. In addition AHP (Analytics Hierarchy Process) was used in order to evaluate the subject characteristic applied to each related to through more objective methods. The analysis results identified in this study such as the quality trust and understandability for an information duality might be the one of the chief elements of success in Mobile Commerce which applies at the present.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.249-261
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• 2011

The rapid growth of e-business market makes new online companies to start and existing offline companies to join in this area. As the number of players of this market grows rapidly, the competition among them is very intense. Many companies invest huge resources to online marketing including search advertisement, email advertisement and banner advertisement. Because these traditional online marketing activities mainly focus on how to invite visitors to their web sites, ROI of these marketing activities are getting lower. Many companies are looking for a new marketing method to escape this situation. In this paper, we propose ROMS (Realtime Online Marketing System) which supports tools to improve conversion ratio of e-commerce sites, ROMS gathers behavioral data of visitors and analyzes it in realtime. ROMS supports live chats, visitor profiling, context analysis, event detection, and live marketing. With ROMS, personalized offers based on visitors' realtime context can be made for each visitor.

• Journal of the Korean Institute of Gas
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• v.24 no.5
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• pp.47-55
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• 2020

Hazardous materials accidents are not limited to the leakage of the material, but if the early response is not appropriate, it can lead to a fire or an explosion, which increases the scale of the damage. However, as the 4th industrial revolution and the rise of the big data era are being discussed, systematic analysis of hazardous materials accidents based on new techniques has not been attempted, but simple statistics are being collected. In this study, we perform the systematic analysis, using machine learning, on the fire accident data for the past 11 years (2008 ~ 2018), accumulated by the National Fire Service. The analysis results are visualized and presented through text mining analysis, and the possibility of developing a damage-scale prediction model is explored by applying the regression analysis method, using the main factors present in the hazardous materials fire accident data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.176-182
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• 2018

In order to understand and track the trends of construction safety accident, this study shows the topic trends in the construction safety accident with LDA(Latent Dirichlet Allocation)-based topic modeling method for data analytics. Especially, it performs to figure out the main issue of construction safety accident with unstructured data analysis based on the topic modeling rather than a variety of structured data analysis for preventing to safety accident in construction industry. To apply this methodology, I randomly collected to 540 news article data about construction accident from January 2017 to February 2018. Based on the unstructured data with the LDA-based topic modeling, I found the 10 topics and identified key issues through 10 keyword in each 10 topics. I forecasted the topic issue related to construction safety accident based on analysis of time-series trends about the news data from January 2017 to February 2018. With this method, this research gives a hint about ways of using unstructured news article data to anticipate safety policy and research field and to respond to construction accident safety issues in the future.