• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.20-22
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• 2015

Recently, the study of smart phone user habits has become a highly focused topic due to the rapid growth of the smart phone market. Indeed, sequential pattern analysis methods were efficiently used for web-based user habit mining long time ago. However, by means of simulations, it has been observed that these methods might fail for smart phone-based user habit mining. In this paper, we propose a novel approach that leads to a considerably increased performance of the traditional sequential pattern analysis methods by reasonably cutting off each chronological sequence of user logs on a device into shorter ones, which represent the sequential user activities in various periods of a day.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.191-202
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• 2003

This paper presents a design and implementation example of intelligent equipment management system that is constructed to manage high price equipment of digital content department effectively. To support system operation we executed data mining and presented various rules that appear in dat3 mining process based on dat3 of user, equipment and using record. We presented personalization plan of web site to offer user dependent administration policy and dynamic interface using analyzed informatio.

• Asian Journal of Innovation and Policy
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• v.12 no.3
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• pp.304-322
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• 2023

Text data mining ('big data methods') is one of the most widely used approaches during the COVID-19 pandemic. In particular, text data mining on Scopus databases or Web of Science (WoS). Text data mining is widely used to collect literature for later bibliometric analysis, and in the end, it becomes a literature review article. Therefore, in this article, we reveal the trend of publication of literature reviews in Scopus journals from Indonesia, Japan, South Korea, Vietnam, Singapore, and Malaysia. This article describes two essential parts, namely 1) a comparison of international publication trends and subject area of literature review publications, and 2) a comparison of Top 5 for Authors, Affiliation, Source Title, and Collaboration Country.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.646-653
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• 2016

Outbound market is a rapidly growing global industry, and has evolved into a 11 trillion won trade. A lot of recommender systems, which are based on collaborative and content filtering, target the existing purchase log or rely on studies based on similarity of products. These researches are not highly efficient as data was not obtained in advance, and acquiring the overwhelming amount of data has been relatively slow. The characteristics of an outbound product are that it should be purchased at least twice in a year, and its pricing should be in the higher category. Since the repetitive purchase of a product is rare for the outbound market, the old recommender system which profiles the existing customers is lacking, and has some limitations. Therefore, due to the scarcity of data, we suggest an improved customer-profiling method using web usage mining, algorithm of association rule, and rule-based algorithm, for faster recommender system of outbound product.

• International Journal of Advanced Culture Technology
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• v.1 no.1
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• pp.11-14
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• 2013

In this paper, we propose a prototype of the SpeechWeb application using the information selection agent. We describe its design and implementation method and illustrated the processing results with the aid of some screenshots. Proposed SpeechWeb application presents the associated contents to the user by the aid of dynamic voice-anchors. These contents are presented using the apriori algorithm, which is one of data mining techniques. The application is better than the existing user-initiative structure from the viewpoint of making the user's interesting induction. Moreover, we believe that our proposed application is effective in information retrieval through wired and wireless telephone networks.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.39-51
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• 2002

In this paper, we propose a poll system on the interned. This poll system makes use of APM which are useful in web and PC using for a server. These tools are all free to obtain, so we can construct this system with the minimum computing environment and the minimum cost. We mention merits and demerits about interned survey and propose how to overcome using this system, and utilize web log data to get an additional information of panel. Finally, we suggest extensibilities of internet survey and the proposed system

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.395-398
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• 2017

We propose a web crawler system with keyword extraction function in this paper. Researches on the keyword extraction in existing text mining are mostly based on databases which have already been grabbed by documents or corpora, but the purpose of this paper is to establish a real-time keyword extraction system which can extract the keywords of the corresponding text and store them into the database together while grasping the text of the web page. In this paper, we design and implement a crawler combining RAKE keyword extraction algorithm. It can extract keywords from the corresponding content while grasping the content of web page. As a result, the performance of the RAKE algorithm is improved by increasing the weight of the important features (such as the noun appearing in the title). The experimental results show that this method is superior to the existing method and it can extract keywords satisfactorily.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.4-6
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• 2001

In this paper, we designed a system that can mine user's traversal patterns from web log files. The system cleans an input data, transactions of a web log file, and finds traversal patterns from the transactions, each of which consists of one user's access pages. The resulting traversal patterns are shown on a web browser, which can be used to analyze the patterns in visual form by a system manager or data miner. We have implemented the system in an IBM personal computer running on Windows 2000 in MS visual C++, and used the MS SQL Server 2000 to store the intermediate files and the traversal patterns which can be easily applied to a system for knowledge discovery in databases.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.117-127
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• 2005

Numerous internet pop advertisement are being provided according to the rapid development of e-commercial and a rise in users. However, it has not been based on analysis of users' inclination but just one-sided providing. With that reason, many web-site provider want to advertis e more efficient and distinguished Internet-advertisement as analyzing Server's Log accessed. In this thesis, we have studied and tested relatively simply adoption system to provide personalized advertisement service. In order to influence personal disposition to system as the most effective way, it first of all uses History files as source data and after refining it, it can search not only visitors' inclination but also the others' visit-list on the other server. As a result of it, it can make advertisement more reality and activity.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.1-11
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• 2018

Recently, the volume of online shopping market continues to be fast-growing, that is important to provide customized service based on customer behavior evaluation analysis. The existing systems only provide analysis data on the profiles and behaviors of the consumers, and there is a limit to the processing in real time due to disk based mining. There are problems of accuracy and system performance problems to apply existing systems to web services that require real-time processing and analysis. Therefore, The system proposed in this paper analyzes the web click log streams generated in real time to calculate the concentration level of specific products and finds interested customers which are likely to purchase the products, and provides and intensive promotions to interested customers. And we verify the efficiency and accuracy of the proposed system.