• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.35-45
• /
• 2012

Researchers and scientists spend huge amount of time in analyzing the previous studies and their results. In order to timely take the advantageous position, they usually analyze various resources such as paper, patents, and Web documents on recent research issues to preoccupy newly emerging technologies. However, it is difficult to select invest-worthy research fields out of huge corpus by using the traditional information search based on keywords and bibliographic information. In this paper, we propose a method for efficient creation, storage, and utilization of semantically relevant information among technologies, products and research agents extracted from 'big data' by using text mining. In order to implement the proposed method, we designed an ontology that creates technological knowledge for semantic web environment based on the relationships extracted by text mining techniques. The ontology was utilized for InSciTe Adaptive, a R&D trends analysis and forecast service which supports the search for the relevant technological knowledge.

• Convergence Security Journal
• /
• v.15 no.4
• /
• pp.113-119
• /
• 2015

Recent, cyber violence is increasing in a school and the severity of the problems encountered day by day. In particular, the severity of the cyber force using the smart phone is recognized as a very high and great problems socially. Cyberbullying have long damage degree and a wide range time duration against of existed physical cyber violence. Then student's affects is very seriously. Therefore, we analyzes the relationship and languages in the classroom for students to use to identify signs of cyber violence that may occur between friends in the class. And we support this information to identified parent, classroom teachers and school sheriff for prevent cyberbullying accidents in the school. For this research, we will design and implement a messenger in the cyber classroom. It have many components that are Big-data vocabulary, analyzer, and communication interface. Our proposed messenger can analyze lingual sign and friendship between students using Big-data analysis method such as text mining. It can analysis relationship by per-student, per-classroom.

• Information Systems Review
• /
• v.8 no.2
• /
• pp.119-138
• /
• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• Journal of the military operations research society of Korea
• /
• v.34 no.2
• /
• pp.79-101
• /
• 2008

This study is for improvement of repair part demand forecasting method of Republic of Korea Air Force aircraft. Recently, demand prediction methods are Weighted moving average, Linear moving average, Trend analysis, Simple exponential smoothing, Linear exponential smoothing. But these use fixed weight and moving average range. Also, NORS(Not Operationally Ready upply) is increasing. Recommended method of Box-Jenkins' ARIMA can solve problems of these method and improve estimate accuracy. To compare recent prediction method and ARIMA that use mean squared error(MSE) is reacted sensitively in change of error. ARIMA has high accuracy than existing forecasting method. If apply this method of study in other several Items, can prove demand forecast Capability.

• The KIPS Transactions:PartD
• /
• v.10D no.6
• /
• pp.897-906
• /
• 2003

The traditional animal phylogenetic tree is to align the body structure of the animal phylums from simple to complex based on the initial development character. Currently, molecular systematics research based on the molecular, it is on the fly, is again estimating prior trend and show the new genealogy and interest of the evolution. In this paper, we generate the training set which is obtained from a DNA sequence ans apply to the classification. We made use of the mitochondrial DNA for the experiment, and then proved the accuracy using the MEGA program which is anaysis program, it is used in the biology field. Although the result of the mining has to proved through biological experiment, it can provede the methodology for the efficient classify and can reduce the time and effort to the experiment.

• Journal of the Korea Society for Simulation
• /
• v.22 no.3
• /
• pp.55-69
• /
• 2013

Managers are required to adopt and implement the human resource management practice that fit firm's strategy the most, so that optimize overall performance. However, the time and relative resources that any firm has are limited, which demands managers to understand the relative importance of all sorts of HR practice and promote them in an order of their relative importance. This study follows the universal perspective and contingency perspective(according to firm size and strategy type), try to identify the most effective HR practice on performance as well as their relative importance by "CART Ensemble" analysis. The results are as follows. From universal perspective, firms always need to high level of integration between strategy and HR department, decision making participation, autonomy of speed of working, and autonomy of way of working. Contingency perspective also suggested the importance of integration between HRM and strategy. But others are different case by case. This study suggests useful implications for managers.

• Journal of Digital Convergence
• /
• v.14 no.12
• /
• pp.237-243
• /
• 2016

Since realtime search keywords of portal sites are arranged in descending order by instant increasing rates of search numbers, they easily show issues increasing in interests for a short time. But they have the limits extracted different results by portal sites and not shown issues by a period. Thus, to find key issues from the whole realtime search keywords for certain period, and to show results of summarizing them and analyzing differences, is significant in providing the basis of understanding issues more practically and in maintaining consistency of them. This paper analyzes differences of week key issues extracted from week analysis of realtime search keywords provided by two typical portal sites. The results of experiments show that the portal group means of realtime search keywords by the independent t-test and the survival functions of realtime search keywords by the survival analysis are statistically significant differences.

• The Journal of Bigdata
• /
• v.5 no.1
• /
• pp.181-188
• /
• 2020

As the size of the airport terminal grows in line with the rapid growth of aviation passengers, the advanced baggage handling system that combines various data technologies has become an essential element in order to handle the baggage carried by passengers swiftly and accurately. Therefore, this study introduces the method of analyzing the baggage handling capacity of domestic airports through the latest data analysis methodology from the process point of view to advance the operation of the airport BHS and the main points based on event log data. By presenting an accurate load prediction method, it can lead to advanced BHS operation strategies in the future, such as the preemptive arrangement of resources and optimization of flight-carrousel scheduling. The data used in the analysis utilized the APIs that can be obtained by searching for "Korea Airports Corporation" in the public data portal. As a result of applying the method to the domestic airport BHS simulation model, it was possible to confirm a high level of predictive performance.

• Journal of Digital Convergence
• /
• v.17 no.12
• /
• pp.255-260
• /
• 2019

Real-time search keywords are not only limited to search keywords that are rapidly increasing interest in real-time, but also have a limitation that they are difficult to determine the sustainability as there is a difference in ranking between portal sites. Estimating sustainability for real-time search keywords is significant in terms of overcoming these limitations and providing some predictability. In particular, long-term search keywords that last for more than a month are of high value as long-lasting social issues. Therefore, in this paper, we analyze the interest based on the ranking of the real-time search keywords and the duration based on sustained weeks, days and hours of real-time search keywords by each portal site and the integrated portal site, and then estimating sustainability based on high level of interest and duration, and present a method to derive real-time search issues with high long-term sustainability.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10b
• /
• pp.826-828
• /
• 2003

이제까지 Protein이나 RNA와 같은 분자의 구조는, 대부분 X-ray crystallography나 Nuclear Magnetic Resonance (NMR) 방법을 통해 분석이 이루어 졌다. 이 방법들은 실제 분자를 직접 원자레벨에서 분석하는 방법으로, 분자를 구성하는 모든 원자의 3차원 좌표 정보를 얻어 낼 수 있다. 원자의 3차원 좌표 정보는 분자의 전체적인 모양과 구조를 이해하는데 유용한 정보이다. 하지만, 분자의 구조를 좀 더 완벽히 이해하기 위해서는 원자 레벨의 좌표 정보 보다는 좀 더 높은 차원에서의 구조 정보가 필요하다. 특히 분자의 구조를 예측하거나, 분자들 사이에 결합 관계를 예측하기 위해서는, 원자 레벨의 정보만으로는 필요한 모든 정보를 얻을 수 없다. 이러한 경우, 분자의 2차원 또는 3차원 구조 요소 (structural elements)가 더욱 좋은 정보를 제공해 줄 수 있다. Protein 분자의 경우. 이미 3차원 좌표 정보를 이용해서, 2차원 구조 요소를 알아내는 자동화된 방법이 알려져 있다. 그러나 RNA의 경우 protein에 비해 알려진 결정 구조가 적기 때문에. 아직까지 2차원 구조 요소나 3차원 구조 요소를 알아내는 자동화된 방법이 알려져 있지 않다. 따라서, 이제까지는 RNA의 구조 요소를 알아내기 위해, 사람이 직접 RNA분자의 3차원 좌표 정보를 분석함으로써 많은 시간과 노력이 필요했다. 이 때문에, 우리는 RNA의 원자들의 3차원 좌표 정보를 이용해서, 2차원 구조요소와 3차원 구조 요소 정보를 자동화된 방법으로 밝혀내는 알고리즘을 개발하였다. 우리는 분자를 구성하고 있는 원자들의 3차원 좌표 정보를 Protein data bank (PDB)에서 가져왔다. 우리의 알고리즘은 PDB file형태의 데이터라면 protein-RNA 복합체나 RNA 분자 모두에서 RNA의 2차원 구조 요소나 3차원 구조 요소를 얻어낼 수 있다. 우리의 연구는 RNA의 원자레벨의 3차원 좌표 정보를 이용해서 RNA의 구조 요소를 뽑아내는 첫 번째 시도로, 우리의 알고리즘을 통해 얻어진 구조 정보는 RNA의 구조 예측 연구나. protein-RNA complex의 결합 예측 연구에 많은 도움을 줄 수 있으리라 기대된다.