• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.298-305
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• 2009

In contrast to content_based filtering systems, collaborative filtering systems not only don't contain information of items, they can not recommend items when users don't provide the information of their interests. In this paper, we propose the recommender agent using association item tree to solve the shortcomings of collaborative filtering systems. Firstly, the proposed method clusters users into groups using vector space model and K-means algorithm and selects group typical rating values. Secondly, the degree of associations between items is extracted from computing mutual information between items and an associative item tree is generated by group. Finally, the method recommends items to an active user by using a group typical rating value and an association item tree. The recommender agent recommends items by combining user information with item information. In addition, it can accurately recommend items to an active user, whose information is insufficient at first rate, by using an association item tree based on mutual information for the similarity between items. The proposed method is compared with previous methods on the data set of MovieLens recommender system.

• The Journal of the Korea Contents Association
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• v.7 no.10
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• pp.19-26
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• 2007

Since collaborative filtering has used the nearest-neighborhood method based on item preference it cannot only reflect exact contents but also has the problem of sparsity and scalability. The item-based collaborative filtering has been practically used improve these problems. However it still does not reflect attributes of the item. In this paper, we propose the method of associative group using the FP-Tree to solve the problem of existing recommendation system. The proposed makes frequent item and creates association rule by using FP-Tree without occurrence of candidate set. We made the efficient item group using $\alpha-cut$ according to the confidence of the association rule. To estimate the performance, the suggested method is compared with Gibbs Sampling, Expectation Maximization, and K-means in the MovieLens dataset.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.30-36
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• 2001

We present a new algorithm for mining association rules in the large database. Association rules are the relationships of items in the same transaction. These rules provide useful information for marketing. Since Apriori algorithm was introduced in 1994, many researchers have worked to improve Apriori algorithm. However, the drawback of Apriori-based algorithm is that it scans the transaction database repeatedly. The algorithm which we propose scans the database twice. The first scanning of the database collects frequent length l-itemsets. And then, the algorithm scans the database one more time to construct the data structure Common-Item Tree which stores the information about frequent itemsets. To find all frequent itemsets, the algorithm scans Common-Item Tree instead of the database. As scanning Common-Item Tree takes less time than scanning the database, the algorithm proposed is more efficient than Apriori-based algorithm.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.6
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• pp.683-697
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• 2012

In this paper, a risk analysis methodology applicable to shield TBM tunnels was studied. Fault Tree Analysis (FTA) was utilized to identify all risk items and to calculate the probability of failure of each item and Analytic Hierarchy Process (AHP) was used to obtain the impact of each risk item. Finally, a risk level of each risk item can be assessed. Developed methodology is applied to a Seoul subway site in which EPB shield tunnel method was utilized and it was found that risk analysis results matched reasonably well with field data.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.197-206
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• 2012

A exisiting recommedation system using association rules has the problem, such as delay of processing speed from a cause of frequent scanning a large data, scalability and accuracy as well. In this paper, using a Implicit method which is not used user's profile for rating, we propose the personalized recommendation system which is a new method using the FP-tree mining based on RFM. It is necessary for us to keep the analysis of RFM method and FP-tree mining to be able to reflect attributes of customers and items based on the whole customers' data and purchased data in order to find the items with high purchasability. The proposed makes frequent items and creates association rule by using the FP-tree mining based on RFM without occurrence of candidate set. We can recommend the items with efficiency, are used to generate the recommendable item according to the basic threshold for association rules with support, confidence and lift. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.6
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• pp.667-681
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• 2012

In general, risk management consists of a series of processes or steps including risk identification, risk analysis, risk evaluation, risk mitigation measures, and risk re-evaluation. In this paper, potential risk factors that occur in shield TBM tunnels were investigated based on many previous case studies and questionaries to tunnel experts. The risk factors were classified as geological, design or construction management features. Fault Tree was set up by dividing all feasible risks into four groups that associated with: cutter; machine confinement; mucking (driving) and segments. From the Fault Tree Analysis (FTA), 12 risk items were identified and the probability of failure of each chosen risk item was obtained.

• Korean Journal of Organic Agriculture
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• v.21 no.4
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• pp.589-600
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• 2013

The Purpose of this paper is to analysis on consumer's purchasing behavior and intention of local food. To analysis consumer's purchasing behavior, a series of homemaker surveys were conducted. The sample size of the survey is 416 respectively. As a survey result, consumer's purchasing behavior shows that purchasing ratio of local food and buying place is various type. By decision tree model analysis showed that consumer's purchasing intention is enough to establishing local food system in region. Therefore, strategies for regional consumption are needed expression of the place city and county of origin, diversification of purchasing item and buying area, and sustainable improvement for safety and trust on local food.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.34-41
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• 2016

The purpose of this paper is to conduct ETA on six items of ESS: the whole system, battery, BMS, PCS, ESS and cable. To achieve that, ESS work flow and its components are categorized. Based on performance, human, environmental, management, and safety, this paper drew initiation events (IE) and end states (ES). ETA is applied to the main functions of each item, and the end states that may occur in one initiation event are suggested. In addition, detailed classification was performed to induce various end states on the basis of the suggested initiation events ; loss of grid electricity of ESS, loss of battery electricity(DC) of battery, impairment of electric function of BMS, loss of grid electricity(AC) of PCS, loss of data of EMS, Mechanical damage of cable, event sequence analysis conducted on the basis of event trees. If the suggested IEs and ESs are applied on the basis of ESS event cases, it is expected to prevent the same kinds of accident and operate ESS safely.

• Journal of the Korean Dietetic Association
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• v.22 no.3
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• pp.193-213
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• 2016

The purpose of this study is to provide a standard job description for a nutrition teacher placed in primary and secondary schools by analyzing their duties. DACUM is an acronym for 'Developing A CUrriculuM'. It was used by experts to determine the job duties, tasks and task elements to establish the job descriptions of a nutrition teachers through the development of a DACUM chart. An expert panel consisting of 10 nutrition teachers participated in a DACUM workshop and derived nutrition teacher's DACUM chart. A total of 1,550 nutrition teachers across the country were targeted as the survey subjects for validation of the DACUM chart through their perception of the frequency, importance, and difficulty of each item in the job description. A tree structure, criticality analysis, and contents validity index were added for verification. The definition of the nutrition teacher's job and DACUM chart with 5 duties, 28 tasks, and 107 task elements were derived by the DACUM method. The definition of a nutrition teacher was 'A teacher who is responsible for food service management and nutrition education and counseling for health promotion and disease prevention for students in primary and secondary schools'. The validation results of the tree structure were the priorities of the 28 tasks with ranks 1 and 2. Because there was no third priority, it was considered to be a good representation of the tasks of nutrition teachers. The DACUM chart was found to be evenly distributed with relative importances of more than 17 or less than 11 through the criticality analysis. Since the C5-4 (Conduct simulation exercise against food poisoning)'s content validity index was significantly less than the reference value of 0.78, it was not included in the final job description. 5 duties, 28 tasks, 102 task elements were included in the final job description of a nutrition teacher.

• Korean Journal of Biological Psychiatry
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• v.15 no.4
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• pp.303-309
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• 2008

Objectives : Some reports have suggested that 5-HT5A polymorphism allelic association was associated with depression, however, there has been no report about relationship between the 5-HT5A gene and antidepressant response. We conducted the association study of the 5-HT5A receptor gene polymorphisms (-19G/C,12A/T) and response to citalopram in Korean patients with major depressive disorder(MDD). Methods : A total of 106 patients with major depressive disorder were included in this study. The patient's symptoms were measured by 21-item Hamilton Depression Rating Scale(HAMD) at baseline, week 1, week 2, week 4 and week 8 during citalopram treatment. A Responder to citalopram was defined by 50% reduction of total HAMD scores. To analyze genetic polymorphisms, a polymerase chain reaction based method was used. Results : At week 8, responders were 62, non-responders were 44. No significant differences of genotypes or allelic association in 19G/C and 12A/T polymorphisms were observed between responsive and non-responsive patients. Conclusion : These results do not support the hypothesis that this polymorphism of the HT5A receptor gene is involved in the therapeutic response to citalopram.