• Journal of the Korean Operations Research and Management Science Society
• /
• v.28 no.3
• /
• pp.135-148
• /
• 2003

In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.

• The Journal of Korean Association of Computer Education
• /
• v.6 no.2
• /
• pp.107-120
• /
• 2003

In Web Based Instruction, as evaluation of learning process means individual student's learning activity, it demands data on learning time, pattern, participation, environment in a specific learning contents. The purpose of this paper is to reflect analysis results of individual student's learning status in achievement evaluation using the most suitable web log mining to settle evaluation problem of learning process, an issue in web based instruction. The contents and results of this study are as following. First, conformity item for learning status analysis is determined and web log data preprocessing is executed. Second, on the basis of web log data, I construct student's database and analyze learning status using data mining techniques.

• Journal of Korea Multimedia Society
• /
• v.10 no.9
• /
• pp.1106-1116
• /
• 2007

Recently e-commerce trade on the web has grown rapidly in scale and complexity, just as web site designs and web servers have become more complicated. In view of these complexities, it is obviously difficult to analyse web user's data since they web users employ so many different web paths. The existing association rule investigation algorithms identify all items with a high correlation. However even though users often only want to find items in which they have interest, it is still difficult to find the rules they want out of all of the many association rules found by existing algorithms. In this paper, we propose a system linking each node with the sequence association rule, linking all routes after finding a path corresponding to a user with the association rule-one of the data mining techniques which identify user patterns in web user paths. The suggested system helps us construct individualized or customer-subdivided sites using the sequence association rule in order to harmonize the paths of web users with user characters.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 2007.11a
• /
• pp.285-292
• /
• 2007

The parallel corpus is an important resource in the research field of data-driven natural language processing, but there are only a few parallel corpora publicly available nowadays, mostly due to the high labor force needed to construct this kind of resource. A novel strategy is brought out to automatically fetch parallel text from the web in this paper, which may help to solve the problem of the lack of parallel corpora with high quality. The system we develop first downloads the web pages from certain hosts. Then candidate parallel page pairs are prepared from the page set based on the outer features of the web pages. The candidate page pairs are evaluated in the last step in which the sentences in the candidate web page pairs are extracted and aligned first, and then the similarity of the two web pages is evaluate based on the similarities of the aligned sentences. The experiments towards a multilingual web site show the satisfactory performance of the system.

• The KIPS Transactions:PartD
• /
• v.16D no.5
• /
• pp.673-682
• /
• 2009

XML data are widely used for data representation and exchange on the Web and the data type is an continuous stream in ubiquitous environment. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the sliding window. XML stream data are modeled as a tree set, called XFP_tree and we quickly extract the frequent structures over recent XML data in the XFP_tree.

• Journal of Internet Computing and Services
• /
• v.10 no.5
• /
• pp.95-105
• /
• 2009

There are various studies to provide useful information for users on huge data of web-sites. Web usage mining among them is a method to extract meaningful patterns based on web users' log data. Most of existing patterns of web usage mining, however, had not considered users' diverse inclination but created general models. Web users' keywords can have various meaning upon their tendency and background knowledge. This study is for generating Multi Concept Keyword Model (MCK-Model) by analyzing web usage information on users' keywords of interest. MCK-Model can supply web page network for various inclination based on users' keywords of interest. Also, MCK-Model can be used to recommend the most proper web pages and it has been confirmed that the suggested method is useful enough.

• Journal of Korea Society of Industrial Information Systems
• /
• v.16 no.2
• /
• pp.19-29
• /
• 2011

Due to the development of web technologies and the increasing use of smart devices such as smart phone, in recent various web services are widely used in many application fields. In this environment, the topic of supporting personalized and intelligent web services have been actively researched, and an analysis technique on a web-click stream generated from web usage logs is one of the essential techniques related to the topic. In this paper, for efficient analyzing a web-click stream of sequences, a sequential pattern mining technique is proposed, which satisfies the basic requirements for data stream processing and finds a refined mining result. For this purpose, a concept of interesting sequential patterns with a time-interval constraint is defined, which uses not on1y the order of items in a sequential pattern but also their generation times. In addition, A mining method to find the interesting sequential patterns efficiently over a data stream such as a web-click stream is proposed. The proposed method can be effectively used to various computing application fields such as E-commerce, bio-informatics, and USN environments, which generate data as a form of data streams.

• Journal of Information Technology Applications and Management
• /
• v.11 no.2
• /
• pp.227-237
• /
• 2004

While the WWW offers an incredibly rich base of information, organized as a hypertext, it does not provide a uniform and efficient way to retrieve specific information. When one tries to find information entering several query terms into a search engine, the highly-ranked pages in the result usually contain many irrelevant or useless pages. The problem is that single-term queries do not contain sufficient information to specify exactly which web pages are needed by the user. The purpose of this paper is to describe the employment of association rules in data mining for developing networks and computing associative coefficient among the terms. And this paper shows how the dynamic query expansion and/or reduction can be performed in information retrieval.

• Journal of Korean Society for Quality Management
• /
• v.32 no.2
• /
• pp.93-108
• /
• 2004

The purpose of this research is to summarize the methodological issues in internet survey and to suggest personalized internet survey system using data mining technique for enhancing the survey quality of internet survey as well as utilizing the benefit of interactive multimedia factors of internet survey. The data mining technique used in this paper is Case Based Reasoning for adopting individual design preference affecting survey quality. For achieving the research purpose, two surveys, pre & post survey, were performed. Pre survey was done for implementing CBR database to find individual index affecting survey quality and post survey was used for measuring the peformance of personalized internet survey system. The result shows that the survey quality of personalized web survey system is better than generalized web survey system.

• Journal of Korea Multimedia Society
• /
• v.6 no.4
• /
• pp.707-713
• /
• 2003

Convenience and promptness of the internet have been not only making the electronic commerce grow rapidly in case of website, analyzing a navigation pattern of the users has been also making personalization and customization techniques develop rapidly for providing service accordant to individual interestingness. Web personalization and customization skill has been utilizing various methods, such as web log mining to use web log data and web mining to use the transaction of users etc, especially e-CRM analyzing a navigation pattern of the users. In this paper, We measure exact duration time of the users in web page and web site, compute weight about duration time each page, and propose a way to comprehend e-loyalty through the computed weight.