• 전자공학회논문지 IE
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• v.43 no.1
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• pp.67-72
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• 2006

According to the growth of wireless networks, and the spread of mobile devices, the provision of recommender services to help consumers find items to purchase with the use of the suited contexts is an important issue in mobile commerce. In this paper, we propose a proactive mobile commerce service that enables a consumer to obtain relevant information efficiently by using differentiated recommendation in context-aware environment. This paper describes the recommendation method and presents grocery shopping application prototype that implement the method. Several experiments are performed and the results verify that the proposed method's recommendation performance is better than other existing methods.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.161-171
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• 2008

The most important reason for increasing web traffic and overloaded web servers is a dramatic growth of web users which leads to a great dissatisfaction of each individual user. For overcoming this situation, studies for an acceleration of web content have been conducted actively. We use web caching technology for reducing the load of the web system and traffic in the network. In this paper, we proposed a new web caching technology with the related web object which based on the unit of web processing and characteristics of the web object. Also we verified the availability of the proposed system with comparison and experiments.,

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.47-52
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• 2005

The context-aware retrieval method is one of the fundamental characteristics in ubiquitous computing. The essential aims of context-aware retrieval method are retrieving relevant information and delivering information quickly. We propose a new method that retrieves relevant information and delivers information quickly using characteristics of levelized contexts. We extract rules and recommendation information in the near future using context values and rules. Then we prefetch recommendation information in very near future using access score. Our method retrieves relevant information and deliver information quickly by storing only recommendation information to be needed in near future using the characteristics of levelized contexts.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1189-1202
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• 1999

As compared with VOD data, NOD article data has the following characteristics: it is created at any time, has a short life cycle, is selected as not one article but several articles by a user, and has high access locality in time. Because of these intrinsic features, user access patterns of NOD article data are different from those of VOD. Thus, building NOD system using the existing techniques of VOD system leads to poor performance. In this paper, we analysis the log file of a currently running electronic newspaper, show that the popularity distribution of NOD articles is different from Zipf distribution of VOD data, and suggest a new popularity model of NOD article data MS-Zipf(Multi-Selection Zipf) distribution and its approximate solution. Also we present a life cycle model of NOD article data, which shows changes of popularity over time. Using this life cycle model, we develop LLBF (Largest Life-cycle Based Frequency) prefetching algorithm and analysis he performance by simulation. The developed LLBF algorithm supports the similar level in hit-ratio to the other prefetching algorithms such as LRU(Least Recently Used) etc, while decreasing the number of data replacement in article prefetching and reducing the overhead of the prefetching in system performance. Using the accurate user access patterns of NOD article data, we could analysis correctly the performance of NOD server system and develop the efficient policies in the implementation of NOD server system.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1066-1077
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• 2004

Dramatic increase in the number of Internet users want highly qualified service of continuous media contents on the web. To solve these problems, we present two network caching schemes(PPC, PPCwP) which consider the characteristics of continuous media objects and user access pattern in this paper. While there are plenty of reasons to create rich media contents, delivering this high bandwidth contents over the internet presents problems such as server overload, network congestion and client-perceived latency. PPC scheme periodically calculates the popularity of objects based on the playback quantity and determines the optimal size of the initial fraction of a continuous media object to be cached in proportion to the calculated popularity. PPCwP scheme calculates the expected popularity using the series information and prefetches the expected initial fraction of newly created continuous media objects. Under the PPCwP scheme, the initial client-perceived latency and the data transferred from a remote server can be reduced and limited cache storage space can be utilized efficiently. Trace-driven simulation have been performed to evaluate the presented caching schemes using the log-files of iMBC. Through these simulations, PPC and PPCwP outperforms LRU and LFU in terms of BHR and DSR.