• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.717-730
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• 2004

Recently. many researches on the personalization of a web-site have been actively made. The web personalization predicts the sets of the most interesting URLs for each user through data mining approaches such as clustering techniques. Most existing methods using clustering techniques represented the web transactions as bit vectors that represent whether users visit a certain WRL or not to cluster web transactions. The similarity of the web transactions was decided according to the match degree of bit vectors. However, since the existing methods consider only whether users visit a certain URL or not, users' interestingness on the URL is excluded from clustering web transactions. That is, it is possible that the web transactions with different visit proposes or inclinations are classified into the same group. In this paper. we propose an enhanced transaction modeling with interestingness weight to solve such problems and a new similarity measuring method that exploits the proposed transaction modeling. It is shown through performance evaluation that our similarity measuring method improves the accuracy of the web transaction clustering over the existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.1007-1014
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• 2003

It is important to integrate an enterprise application for automating of the business profess, which is responded by a flow of market environment. There are two categories of method that integrate enterprise applications. One is Synchronous Integration, and the other is Asynchronous Integration. EAI(Enterprise Application Integration) and Web service which of the asynchronous integration is focused in the automating method of the business process. After we construct the application integration for automating of the business process, we have to concern about managing of the business transaction. Many Organizations have proposed the process method of business transaction based on 2-phase commit protocol. But this method can′t supply the phase that classify the transaction by transaction weight. In this paper, we propose an efficient method of transaction process for business transactions, which is composed by ′Classify Phase′ that classify transactions. We called this model "3-Phase Commit Method Applied by Classify Phase", we design this model to manage an resource of enterprise efficiently. The proposed method is compared by the method based on 2-Phase commit that could be a problem of management the resource of enterprise, and the advantage of this method is certified to propose the solution of that problem.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1053-1068
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• 2003

In this paper, we propose a new scheduling method without timing covert channel of real-time transaction for secure database systems that implement mandatory access control. Our scheduling method use the wait queue based on security level to remove timing covert channel. And it use priority queue that consider transaction type, deadline, and weight. Therefore, the proposed scheduling method prevents timing covert channel because it is kept noninterference between transactions with different security level, and maximizes the sum of the weight of transactions that satisfy its deadline. The simulation results, is a comparison of traditional methods, show that our scheduling method is improved to 30%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1498-1508
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• 2003

It is important to integrate an enterprise application for automating of the business process, which is responded by a flow of market environment. There are two categories of method that integrate enterprise applications. One is Synchronous Integration, and the other is Asynchronous Integration. EAI(Enterprise Application Integration) and Web service which of the asynchronous integration is focused in the automating method of the business process. After we construct the application integration for automating of the business process, we have to concern about managing of the business transaction. Many Organizations have proposed the process method of business transaction based on 2-phase commit protocol. But this method can't supply the phase that classify the transaction by transaction weight. In this Paper, we Propose an efficient method of transaction process for business transactions, which is composed by ‘Classify Phase’ that classify transactions. We called this model “3-Phase Commit Method Applied by Classify Phase”, we design this model to manage an resource of enterprise efficiently. The proposed method is compared by the method based on 2-Phase commit that could be a problem of management the resource of enterprise, and the advantage of this method is certified to propose the solution of that problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.16-23
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• 2005

Purpose of this research wishes to present way to more safe and reliable operation way to shopping mall operation companies as well as consumerism through general utilization present condition of customers and satisfaction investigation that use internet shopping mall and establish wholesome commercial transaction order. This research draws criteria and items about success factor through each precedent research literature investigation about internet shopping mall success factor, and made up a questionnaire criteria and items that affect important internet shopping mall company's selection to college students and graduate students with learning connected with electronic commerce course. Execute pair comparison that require in AHP and analyzed priority weight about criteria and items to shopping mall company selection. As the result, Appeared that 'Credibility about internet shopping mall company's transaction' is considered most heftily by importance criteria at internet shopping mall selection. Appeared that think 'Credibility of personal information leakage prevention' most important to each criteria.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.499-508
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• 2015

High utility itemset(HUI) mining refers to the discovery of itemsets with high utilities which are not less than a user-specified minimum utility threshold, by considering both the quantities and weight factors of items in a transaction database. Recently the utility-list based HUI mining algorithms have been proposed to avoid numerous candidate itemsets and the algorithms need the costly join operations. In this paper, we propose a new HUI mining algorithm, using the utility-list with additional attributes of transaction utility and common utility of itemsets. The new algorithm decreases the number of join operations and efficiently prunes the search space. Experimental results on both synthetic and real datasets show that the proposed algorithm outperforms other recent algorithms in runtime, especially when datasets are dense or contain many long transactions.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.435-442
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• 2004

It is important to integrate an enterprise application for automating of the business process, which is responded by a flow of market environment. There are two categories of method that integrate enterprise applications. One is Synchronous Integration, and the other is Asynchronous Integration. EAI(Enterprise Application Integration) and Web service which of the asynchronous integration is focused in the automating method of the business process. After we construct the application integration for automating of the business process, we have to concern about managing of the business transaction. Many Organizations have proposed the process method of business transaction based on 2-phase commit protocol. But this method can't supply the phase that classify the transaction by transaction weight. In this paper, we propose an efficient method of transaction process for business transactions, which is composed by "Classify Phase" that classify transactions. We called this model "3-Phase Commit Method Applied by Classify Phase, " we design this model to manage an resource of enterprise efficiently. The proposed method is compared by the method based on 2-Phase commit that could be a problem of management the resource of enterprise, and the advantage of this method is certified to propose the solution of that problem.ion of that problem.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.3
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• pp.262-266
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• 2005

In this paper, in order to enhance thrust of slotless type Permanent Magnet Linear Synchronous Motor, an optimal design is achieved by combining a genetic algorithm with 3D space harmonic method. In the case of multi-objective functions, the ratio of thrust/weight and thrust/volume are increased by $\7.56[%]l\;and\;7.98\[%]$, respectively. Thus, miniaturization and lightweight were realized at the same time.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.447-458
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• 2002

In this paper, we design and implement Wireless Transaction Protocol(WTP) and evaluate it for wireless transaction processing in mobile computing environments. The design and implementation of WTP are based on the coroutine model that might be suitable for light-weight portable devices. We test the compatibility between our product and the other products such as Nokia, Kannel and WinWAP For the evaluation of WTP, we use an Internet simulator that can arbitrary generate random wireless errors based on the Gilbert model. In our experiment, the performance of WTP is measured and compared to those of Transmission Control Protocol(TCP) and TCP for Transactions. The experiment shows that WTP outperforms the other two protocols for wireless transaction processing in terms of throughput and delay. Especially, WTP shows much higher performance In ease of high error rate and high probability of burst errors. This comes from the fact that WTP uses a small number of packets to process a transaction compared to the other two protocols and introduces a fixed time interval for retransmission instead of the exponential backoff algorithm. The experiment also shows that the WTP performance is optimized when the retransmission counter is set to 5 or 6 in case of high burst error rate.