• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1093-1102
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• 2003

As the use of internet is growing, the amount of information is increasing rapidly and XML that is a standard of the web data has the property of flexibility of data representation. Therefore electronic document systems based on web, such as EDMS (Electronic Document Management System), ebXML (e-business extensible Markup Language), have been adopting XML as the method for exchange and standard of documents. So research on the method which can manage and search structural XML documents in an effective wav is required. In this paper we propose the clustering method based on structural similarity among the many XML documents, using typical structures extracted from each document by sequential pattern mining in pre-clustering process. The proposed algorithm improves the accuracy of clustering by computing cost considering cluster cohesion and inter-cluster similarity.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.101-121
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• 2010

This paper presents an intelligent prefetching technique that significantly improves performance of hybrid fash-disk storage, a combination of flash memory and hard disk. Since flash memory embedded in a hybrid device is much faster than hard disk in terms of I/O operations, it can be utilized as a 'cache' space to improve system performance. The basic strategy for prefetching is to utilize sequential pattern mining, with which we can extract the access patterns of objects from historical access sequences. We use two techniques for enhancing the performance of hybrid storage with prefetching. One of them is to modify a FAST algorithm for mapping the flash memory. The other is to extend the unit of prefetching to a block level as well as a file level for effectively utilizing flash memory space. For evaluating the proposed technique, we perform the experiments using the synthetic data and real UCC data, and prove the usability of our technique.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.21-32
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• 2021

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly increasing. The increased transactions of electronic prepayment, however, also leads to the increased fraud attempts. It is mainly because electronic prepayment can easily be converted into cash. The objective of this paper is to develop a methodology that can effectively detect fraud transactions in electronic prepayment, by using sequential pattern mining techniques. To validate our approach, experiments on real transaction data were conducted and the applicability of the proposed method was demonstrated. As a result, the accuracy of the proposed method has been 95.6 percent, showing that the proposed method can effectively detect fraud transactions. The proposed method could be used to reduce the damage caused by the fraud attempts of electronic prepayment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.204-209
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• 2002

The interest of data mining in artificial intelligence with fuzzy logic has been increased. Data mining is a process of extracting desirable knowledge and interesting pattern ken large data set. Because of expansion of WWW, web data is more and more huge. Besides mining web contents and web structures, another important task for web mining is web usage mining which mines web log data to discover user access pattern. The goal of web usage mining in this paper is to find interesting user pattern in the web with user feedback. It is very important to find user's characteristic fer e-business environment. In Customer Relationship Management, recommending product and sending e-mail to user by extracted users characteristics are needed. Using our method, we extract user profile from the result of web usage mining. In this research, we concentrate on finding association rules and verify validity of them. The proposed procedure can integrate fuzzy set concept and association rule. Fuzzy association rule uses given server log file and performs several preprocessing tasks. Extracted transaction files are used to find rules by fuzzy web usage mining. To verify the validity of user's feedback, the web log data from our laboratory web server.

• The Journal of Society for e-Business Studies
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• v.10 no.3
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• pp.85-110
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• 2005

OWL-S has a major leadership in the field of Web Service discovery and is being actively studied in LARKS and METEOR-S projects. These researches do not consider all components of OWL-S standards, and it is needed to enhance their discovery algorithms. In this paper, we propose matching algorithms based on process information such as process structure matching, service classification matching and business pattern matching algorithms. We also improve the QoS matching algorithm of METEOR-S project. Finally, we integrate these two kinds of matching algorithms as accommodate users preferences.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.151-153
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• 2006

웹을 이용하는 사용자들은 통상적으로 짧은 시간 내에 포탈의 여러 페이지를 방문하는 현상이 있는데, 이 때 방문하는 각 페이지 상에 위치 정보를 필요로 하는 콘텐츠(위치 기반 광고 배너, 위치 기반 날씨 등)가 존재한다면 웹의 특성상 짧은 시간 내에 동일 IP에 대한 위치 정보 검색을 반복하게 된다. 본 논문에서는 이러한 웹 사용 패턴을 캐시를 통해 반영한 고성능 인터넷 위치 검색을 제안, 구현하고 그 성능을 검증한 것이다. 이는 초당 2-3천 건 이상의 대용량 위치 정보를 검색을 수행하데 특히 적합한 방법으로, 적은 비용으로 위치 검색 성능을 획기적으로 높일 수 있었다.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.75-85
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• 2017

Personalization recommendations have already proven in many areas of the e-commerce industry. For personalization recommendations, additional work such as reclassifying items is generally necessary, which requires personal information. In this study, we propose a recommendation technique that neither exploit personal information nor reclassify items. We focus on music recommendation and performed experiments with actual music listening data. Experimental analysis shows that the proposed method may result in meaningful recommendations albeit it exploits less amount of data. We analyze the appropriate number of items and present future considerations for contextual recommendation.

• Human Ecology Research
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• v.55 no.5
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• pp.555-566
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• 2017

This study analyzes the practical tasks and required competency for technical designers to provide basic data on the training of domestic technical designers. The survey was applied to 21 technical designers of big vendors as well as investigated tasks, task flow, important tasks, time-consuming tasks, and required competencies. The results of the study are as follows. First, the technical designers were in charge of several brands of buyers and distributors of fashion companies, or several lines of the same brand. The main production items were cut and sewn knits. Second, the flow of task and tasks were in the order of buyer comments analysis, sloper decision to matching style, sewing specification, productive sewing method research, size specification suggestion, pattern correction comments, construction decision to matching style & fabric, sample evaluations, fit approval, business e-mail writing, specification & grading confirmation, and communication with buyer. Third, five tasks (analysis of buyer comments analysis, communication with buyer, pattern correction comments, productive sewing methods research, sample evaluation) were important and time-consuming tasks. Fourth, reeducation was required in order of sewing, pattern, English, fabric, and fitting. Fifth, competencies to be a technical designers were fitting, pattern correction, size specification & grading, construction & sewing specification, sewing terms & techniques, and communication skills. In conclusion, technical designer training should focus on technology-based instruction, such as sample evaluation, fitting, pattern correction, and productive sewing methods research of cut and sewn knits.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.757-764
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• 2009

In discriminant analysis, we consider a special pattern which contains a block of missing observations. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider the bootstrap confidence intervals of the error rate in the circular models when the covariance matrices are equal and not equal.

• Journal of Korean Society for Quality Management
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• v.37 no.4
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• pp.10-15
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• 2009

In this paper, we propose new methods which is to determine level of noise factor. Even Taguchi give level of noise factor which is best(or maximum) and worst(or minimum) condition, we give level of noise factor which is representative value by observing noise factor frequency. Sometimes level of noise factor is given one, two and three. We know this method is more fit in real fields.