• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.647-653
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• 2022

Data mining is a technique that explores knowledge such as relationships and patterns between data by exploring and analyzing data. Data that occurs in the real world includes a temporal attribute. Temporal data mining research to find useful knowledge from data with temporal properties can be effectively utilized for predictive judgment that can predict the future. In this paper, we propose an algorithm using time-unit grouping to classify the database into regular time period units and discover frequent pattern itemsets in time units. The proposed algorithm organizes the transaction and items included in the time unit into a matrix, and discovers frequent items in the time unit through grouping. In the experimental results for the performance evaluation, it was found that the execution time was 1.2 times that of the existing algorithm, but more than twice the frequent pattern itemsets were discovered.

• Information Systems Review
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• v.23 no.1
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• pp.1-22
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• 2021

This study aims to analyze online game user's game items transacting behaviors for the two game genres such as MMORPG and sports game. For the sake of conducting the analysis, we adopted a fuzzy logic agent-based modeling. In the online game fields, game items transactions are crucial to game company's profitability. However, there are lack of previous studies investigating the online game user's game items transacting activities. Since many factors need to be addressed in a complicated way, ABM (agent-based modeling) simulation mechanism is adopted. Besides, a fuzzy logic is also considered due to the fact that a number of uncertainties and ambiguities exist with respect to online game user's complex behaviors in transacting game items. Simulation results from applying the fuzzy logic ABM method revealed that MMORPG game users are motivated to pay expensive price for high-performance game items, while sports game users tend to transact game items within a reasonable price range. We could conclude that the proposed fuzzy logic ABM simulation mechanism proved to be very useful in organizing an effective strategy for online game items management and customers retention.

• Journal of Korea Game Society
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• v.5 no.1
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• pp.61-66
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• 2005

The item is an interactive element to escalate interest in the games as well as element providing various satisfactions to players. They give satisfactions to economic desire which is intrinsic in human beings. In this paper we propose an efficient method for item productions and managements by giving name values to items and managing them by database, so that new communities of players could grow with economic systems, which would improve specialties of games as well as solve problems such as hacking, etc.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.115-117
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• 2001

기존의 인터넷 웹사이트에서는 사용자의 만족을 극대화시키기 위하여 사용자별로 개인화 된 서비스를 제공하는 협력적 필터링 방식을 적용하고 있다. 협력적 필터링 기술은 사용자의 취향에 맞는 아이템을 예측하여 추천하며, 비슷한 선호도를 가진 다른 사용자들과의 상관관계를 구하기 위하여 일반적으로 피어슨 상관계수를 많이 이용한다. 그러나, 피어슨 상관계수를 이용한 방법은 사용자가 평가를 한 아이템이 있을 때에만 상관관계를 구할 수 있다는 단점과 예측의 정확성이 떨어진다는 단점을 가지고 있다. 따라서, 본 논문에서는 피어슨 상관관계 기반 예측 기법을 보완하여 보다 정확한 사용자 유사도를 구하는 방법을 제안한다. 제안된 방법에서는 사용자들을 대상으로 사용자가 평가를 한 아이템의 선호도를 사용해서 엔트로피를 적용하였고, 사용자가 선호도를 표시하지 않은 상품에 대해서는 Default Voting 방법을 이용하여 보다 정확한 헙력적 필터링 방식을 구현하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.247-250
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• 2004

지금까지의 라디오는 대부분 음성중심의 프로그램을 전송하였지만 DMB로 개념화되는 라디오와 디지털 기술의 접목은 지금까지 제한적이던 멀티미디어데이터서비스를 확대시키면서 라디오에 시각성을 부여하고 있다. 라디오에 부여되는 시각성은 지금까지의 청각성보다 훨씬 중요한 의미를 가지게 되었다. 이런 추세에 맞춰서 방송 서비스에 대한 멀티미디어데이터서비스 검색 시스템도 시각성을 중심으로 새롭게 재구성되어야 할 필요성이 대두되었다. DMB서비스는 제공되는 콘텐츠에 대해 각기 다른 콘텐츠 정보가 존재하고 이러한 정보를 이용하여 사용자가 원하는 서비스를 비친, 검색하는 방법으로 변화하여야 한다. 본 논문에서는 DMB MOT를 이용하여 MPEG-21 디지털 아이템 메타데이터를 전송하고, 전송된 메타데이터를 이용하여 단말기에 사용자가 원하는 디지털 아이템의 정보를 보여줄 수 있는 브라우징 시스템을 설계하고자 한다.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1593-1601
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• 2017

In a big data platform, association rule mining applications could bring some benefits. For instance, in a agricultural big data platform, the association rule mining application could recommend specific products for farmers to grow, which could increase income. The key process of the association rule mining is the frequent itemsets mining, which finds sets of products accompanying together frequently. Former researches about this issue, e.g. Apriori, are not satisfying enough because huge possible sets can cause memory to be overloaded. In order to deal with it, SON algorithm has been proposed, which divides the considered set into many smaller ones and handles them sequently. But in a single machine, SON algorithm cause heavy time consuming. In this paper, we present a method to find association rules in our Hadoop based big data platform, by parallelling SON algorithm. The entire process of association rule mining including pre-processing, SON algorithm based frequent itemset mining, and association rule finding is implemented on Hadoop based big data platform. Through the experiment with real dataset, it is conformed that the proposed method outperforms a brute force method.

• The Journal of the Korean dental association
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• v.36 no.5 s.348
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• pp.360-364
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• 1998

올해 또다시 6월 9일 치아의 날이 다가왔다. 지난 2월 전국을 떠들썩하게 만들었던 서울치대 교수 임용 비리사건의 악몽을 잊고 국민에게 더욱 가까이 다가갈 수 있는 기회를 맞은 셈이다. 해마다 개최되는 치아의 날 행사에 새로운 아이템의 개발이 필요하다는 목소리가 커지고 있는 시점에서 치아의 날의 역사와 문제점 그리고 개선방향에 대해서 살펴본다.

• Vending industry
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• v.6 no.3 s.18
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• pp.74-76
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• 2006

지난 3월 많은 화제를 뿌리며 등장했던 품목이 핸드북자판기이다. 아이템의 참신성, 자판기만의 전용 콘텐츠로 무장한 핸드북자판기와 과연 시장에서 어떠한 반응을 불러일으키고 있는 지 관심사가 아닐 수 없다. 사업 주체인 희망과 재미사를 찾아 그 궁금중을 풀어 봤다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1183-1190
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• 2017

With the development of network and IT technology, people are searching and purchasing items they want, not bounded by places. Therefore, there are various studies on how to solve the scalability problem due to the rapidly increasing data in the recommendation system. In this paper, we propose an item-based collaborative filtering method using Tag weight and a recommendation technique using MapReduce method, which is a distributed parallel processing method. In order to improve speed and efficiency, the proposed method classifies items into categories in the preprocessing and groups according to the number of nodes. In each distributed node, data is processed by going through Map-Reduce step 4 times. In order to recommend better items to users, item tag weight is used in the similarity calculation. The experiment result indicated that the proposed method has been more enhanced the appropriacy compared to item-based method, and run efficiently on the large amounts of data.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.51-62
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• 2018

Recently, there has been an increasing social concern over the use of random reward game items. In this paper, we try to understand the effect of using random reward game on adolescents based on the survey data over a year. In addition, regression analysis was conducted to examine how socio-psychological variables affect the game addiction of adolescents according to use of random reward games. As a result of analysis, it was found that the random reward game use group had lower self esteem and higher material value than the normal game use group. Also, self esteem and material value have a significant effect on game addiction. And finally, the results and implications were discussed.