• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.139-146
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• 2006

This paper describes the design and implementation details of a distributed transactional workflow monitoring system. There have been prevalent research and development trends in the workflow literature - workflow systems tend to be completely distributed architectures to support very large-scale workflow applications on object-oriented and internet-based infrastructures. That is, the active (object), distributed (architecture), system-oriented (transaction), and large-scale (application) workflow systems are the key targets in terms of the research and development aspects. While the passive, centralized, human-oriented, and small/medium scale workflow systems are the typical instances of the traditional workflow systems. Unlike in the traditional (the client-server architecture) workflow systems, the workflow monitoring features should not be easily supported in the recent (the fully distributed architecture) workflow systems. At the same time, they need a set of additional monitoring features, such as gathering and displaying statistical (or overload status) information of the workflow architectural components dispersed on the internet. We, in this paper, introduce the additional workflow monitoring features that are necessarily required for the recent workflow systems, and show how to embed those features into a web-based distributed workflow system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5B
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• pp.520-530
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• 2004

A multidatabase system (MDBS) is designed to provide universal access to distributed data across multiple autonomous, heterogeneous local database systems (LDBSs). In this paper, we propose a global concurrency control (GCC) algorithm in MDBS. The proposed GCC algorithm adopts the idea of message ordering in group communication messaging system. A necessary condition of GCC algorithm is that global transactions are serialized in the same order at all LDBSs that they execute. n all operations of a transaction are bundled in a single message and the message arrives at LDBSs in the same order using message ordering property, each LDBS can perform subtransactions in the same order. As a result, message ordering allows to determine easily the relative serialization order of global transactions, and then it can support a local autonomy without any information about the serialization order of transactions executing locally.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.147-156
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• 2011

With the increasing utility of the recent information system, the methods to pick up necessary products rapidly by using a lot of data has been studied. Association rule search methods to find hidden patterns has been drawing much attention, and the Apriori algorithm is a major method. However, the Apriori algorithm increases search time due to its repeated scans. This paper proposes an algorithm to reduce searching time of frequent items. The proposed algorithm creates matrix using transaction database and search for frequent items using the mean number of items of transactions at matrix and a defined minimum support. The mean number of items of transactions is used to reduce the number of transactions, and the minimum support to cut down on items. The performance of the proposed algorithm is assessed by the comparison of search time and precision with existing algorithms. The findings from this study indicated that the proposed algorithm has been searched more quickly and efficiently when extracting final frequent items, compared to existing Apriori and Matrix algorithm.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.1-10
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• 1999

A mobile computing environment is one that support user's mobility through the wireless communication technology. Users access the database and get results what they want by running mobile transactions. To run the mobile transaction correctly and to maintain the consistency I database, we need a concurrency control method to schedule transactions, a caching method to manage the cache, and a recovery method to construct a fault tolerant system. A mobile computing system is based on the existing distributed system, but we can't use recovery methods of the existing distributed system directly because of the user's mobility and the features of wireless media. So this paper presents a recovery mechanism to construct a fault tolerant mobile computing systems. Especially. we develop and analyze a recovery algorithm for server failure among types of failure which can arise in mobile computing environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1866-1874
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• 2008

Existing web server lowers the whole capacity of system because of the problem on the processing load of server by closing connection increasing code handshake operation, and remarkable decrease of server capacity if it is the state of overload. Also, there occurs disadvantages of increasing connection tine about client's request and response time because handling of client's multi-requests is not smooth because of thread block and it requests a lot of time and resources for revitalization of thread. Therefore, this paper proposes the extended web server which provides the technique for delay handling and improves the overload of server for better system capacity, communication support, and the unification which is the advantage of web service. And it evaluates the existing system(implemented at Tomcat 5.5) and the proposed mobile web server architecture. The extended server architecture provides excellent exchange condition for system capacity and evaluates improved web server architecture which combines multi-thread with thread pool. The proposed web service architecture in this paper got the better result of improved capacity benefit than the evaluation result of original Tomcat 5.5.

• Korea Trade Review
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• v.42 no.5
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• pp.233-252
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• 2017

The fast changes of global financial environment in recent years increase the risk of trade settlement. This means are required to minimize risk of non payment and to maximize secure payment. Open Account trade accounts for 90% of global trade flows. The O/A system means that the goods, along with all the necessary documents, are shipped and delivered before payment is due, usually within a time frame from 30 to 90 days. Meanwhile, Korean small and medium-sized export enterprises are compelled to globalize their activities owing to limitation and competitiveness of domestic marketplace. To keep face with the global trade settlement system and to support globalization of small and medium-sized export firms, the BPO together with Supply Chain Finance will be solutions. The introduction of the BPO system will allow banks to broaden O/A offerings to their client base and due to secure safety, sellers could ship the goods without delay according to orders and buyers could settle promptly by payment undertaking of correspondent banks. Therefore, it is more effective for companies which have sustainable customers and stable transaction. This study take a look at the trend of the global payment systems and suggested limitation of existed payment in order to derive improvement measures of electronic payment for small and medium-sized export enterprises.

• International Commerce and Information Review
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• v.18 no.2
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• pp.107-127
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• 2016

There has not been enough distribution of documentary evidence of origin at the stage of domestic transaction yet due to the exporter bias of interest in utilizing FTA and shortage of attracting their issues, etc. although about more ten years has passed since Korea-Chile FTA was running. Furthermore, in case of issued and distributed documentary evidence of origin, the accuracy was doubt, so it contains various problems like errors in the certificate of origin issued by the final exporter. Accordingly, this study was to find out the limitations of 'declaration of origin third party confirmation system' operated in order to solve problems of lacking the management ability of origin place of the domestic supplier and improve the accuracy of certificate of origin (comprehensive), and to investigate a method of improvement. To achieve this, this study was to suggest the institutional complementary plans for distribution activation and error prevention on the declaration of origin and introduction plan of loss prevention plan due to the errors in the certificate of origin that the final exporter did not intend in the domestic areas in order to support the use of FTA smoothly for our enterprises.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.91-97
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• 2004

As the electronic commercial transaction is being transacted by contents which can get an illegal intrusion from the outside, we sincerely require security for them. We must consider a protection countermeasure about intrusion from protection of the passive form to protection intrusion of the active one. So the security is required against hackers illegality intrusion into the contents. As soon as the intrusion happens about the contents, the tools providing the monitor of contents are required to minimize the damage to the systems. Modified web contents detection system in this paper prevents the loss of resources and manpower required through individually monitoring on the web. Also, this paper offers rapid support of security that it analyzes the weakness of contents security of the web environment and the cause of the problem with the leakage of information. So this system has the pur pose of protecting the weakness of contents security and the leakage of information.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.