• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.135-139
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• 2008

MMORPG로 대표되는 우리나라 온라인게임의 게임아이템 유형을 보면 대부분이 능력치와 관련된 것들이 많다. 이것은 게임아이템의 일부 기능만을 활용한다는 점에서 보다 적극적으로 게임아이템을 구성하고 그것에 유기적인 역할을 부여할 필요성을 갖게 한다. 이러한 필요성을 충족시키기 위하여 게임아이템을 인지심리학적 관점으로 연구는 것은 매우 유효하다. "게임아이템의 인지프로세스와 지식표상 모델"이라는 것은 인지심리학의 정보처리 과정을 게임아이템 사용자에게 적용하여 구조화한 것이다. 이러한 프로세스와 지식표상 모델은 게임아이템의 명료화와 인과적 플레이를 유도하기 위한 것으로 위의 필요성을 충족시킬 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.151-156
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• 2002

본 논문에서는 MPEG-21 프레임워크 기반 하에 방송용 멀티미디어 컨텐츠를 디지털아이템 선언에 의해 디지털 아이템을 생성하고 이를 소비하기 위한 시스템에 대해 제안하였다. 제안된 시스템은 디지털 아이템을 XML 문서로 생성하고, 이 생성된 디지털 아이템을 소비하기 위한 관련 Parser 모듈들, 브라우저 및 리소스와 관련 데이터 DB로 구성되어 있다. 제안된 시스템을 방송용 컨텐츠에 대해 적용하였으며, 디지털 아이템의 기술을 위해 국제 표준 규격인 PEG-7 MDS 기술자를 이용 적용하였다. 예상 가능한 사용자의 여러 환경 조건을 가상하여 다양한 미디어 리소스를 적용하였다.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1451-1454
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• 2003

본 논문에서는 MPEG-21 에서 정의한 디지털아이템의 파일 포맷의 구조 및 방법을 멀티미디어 파일 포맷으로 제안하였다. 제안한 방법은 디지털아이템을 이진화하는 방법 및 기능, XML로 구성된 디지털아이템 선언(Digital Item Declaration)에서 미디어 리소스를 참조하는 방법 등이다. 제안한 멀티미디어 파일 포맷은 디지털방송, 무선통신, 인터넷 환경에서의 다양한 형태의 컨텐츠들을 효과적이고 체계적으로 조합할 수 있는 기능 및 효과적인 전송 기능을 제공하며, 향후 xml 기반 메타데이터와 미디어리소스를 포함하는 멀티미디어 컨텐츠의 파일 포맷에 대한 참고 모델로서 사용될 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1284-1290
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• 2004

In market-basket analysis, weighted association rule(WAR) discovery can mine the rules which include more beneficial information by reflecting item importance for special products. However, when items are divided into more than one group and item importance for each group must be measured by different measurement or separately, we cannot directly apply traditional weighted association rule discovery. To solve this problem, we propose a novel methodology to discovery the weighted association rule in this paper In this methodology, the items should be first divided into sub-groups according to the properties of the items, and the item importance is defined or calculated only with the items enclosed to the sub-group. Our algorithm makes qualitative evaluation for network risk assessment possible by generating risk rule set for risk factor using network sorority data, and quantitative evaluation possible by calculating risk value using statistical factors such as weight applied in rule generation. And, It can be widely used for new model of more delicate analysis in market-basket database in which the data items are distinctly separated.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1471-1474
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• 2003

MPEG-21 에서 정의된 멀티미디어 프레임워크 하에서 디지털아이템(Digital Item)이 이용자(User) 상호간에 교환되어지고 이용되어지는 상황이 MPEG-21 이 추구하는 궁극적인 목표이다. 이러한 디지털 아이템의 교환과 이용은 IPMP(Intellectual Property Management and Protection), 콘텐츠 취급과 이용, 사건보고(Event Reporting), 효율적인 망과 단말 자원 관리 둥 다양하고 복잡한 활동들을 수반하며 디지털 아이템의 식별과 관련 정보 기술(Description)을 바탕으로 이런 활동들을 효율적으로 수행할 수 있다. 본 논문에서는 MPEG-21의 세 번째 부분인 디지털 아이템 식별(Digital Item Identification)의 일반적인 내용과 DⅡ RA(Registration Authority)에 대해 설명하고 타 식별체계 및 메타데이타 표준과의 관계와 응용분야에 대해에 대해 소개한다. 그리고 DⅡ의 개념을 이용한 식별시스템의 구성과 구축 방법에 대해 논의한다.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.37-38
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• 2012

개인 컴퓨터의 보급과 중앙집중식 처리의 한계로 인해 P2P 기술에 대한 관심이 부각됨에 따라 피어들에 대한 평판을 관리하는 방법들이 연구되고 있다. 본 논문에서는 피어들의 평가와 더불어 피어가 포함하는 아이템들에 대한 평가를 위한 모델을 제안한다. 제안하는 기법은 P2P 환경에서 아이템 공유를 위한 평판 관리 기법 과 악의 피어 검출 방법으로 구성된다. 제안하는 기법은 아이템을 공유하는 피어들 간에 악의 피어에 대한 정보를 상호 교환하여 악의 피어 검출의 정확성을 향상시킨다.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.1-8
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• 2007

In electronic commerce, it is important for users to recommend the proper item among large item sets with saving time and effort. Therefore, if the recommendation system can be recommended the suitable item, we will gain a good satisfaction to the user. In this paper, we proposed the associative relation clustering split method in the collaborative filtering in order to perform the accuracy and the scalability. We produce the lift between associative items using the ratings data. and then split the node group that consists of the item to improve an efficiency of the associative relation cluster. This method differs the association about the items of groups. If the association of groups is filled, the reminding items combine. To estimate the performance, the suggested method is compared with the K-means and EM in the MovieLens data set.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.1-17
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• 2008

Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• Journal of Broadcast Engineering
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• v.8 no.4
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• pp.410-426
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• 2003

MPEG-21 defines a digital item as an atomic unit lot creation, delivery and consumption in order to provide an integrated multimedia framework in networked environments. It is expected that MPEG-21 standardization makes it Possible for users to universally access user's preferred contents in their own way they want. In order to achieve this goal, MPEG-21 has standardized the specifications for the Digital Item Declaration (DID). Digital Identification (DII), Rights Expression Language (REL), Right Data Dictionary (RDD) and Digital Item Adaptation (DIA), and is standardizing the specifications for the Digital Item Processing (DIP), Persistent Association Technology (PAT) and Intellectual Property Management and Protection (IPMP) tot transparent and secured usage of multimedia. In this paper, we design an MPEG-21 terminal architecture based one the MPEG-21 standard with DID, DIA and DIP, and implement with the MPEG-21 terminal. We make a video summarization service scenario in order to validate ow proposed MPEG-21 terminal for the feasibility to of DID, DIA and DIP. Then we present a series of experimental results that digital items are processed as a specific form after adaptation fit for the characteristics of MPEG-21 terminal and are consumed with interoperability based on a PC and a PDA platform. It is believed that this paper has n important significance in the sense that we, for the first time, implement an MPEG-21 terminal which allows for a video summarization service application in an interoperable way for digital item adaptation and processing nth experimental results.