• Journal of Digital Contents Society
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• v.6 no.1
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• pp.1-5
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• 2005

This paper describes the main characteristics of Grid Services based on OGSA and a Grid service for aggregating service data element(SDE)s. In order to build a Grid Service, it needs to consider a systematic building approach from the high-level software architecture that represents the main system components and their interactions. The purpose of this paper is to design and implement an extended service data aggregator service in which SDE is a basic unit for collecting resource information. A GT3 based service data aggregator service is extended to apply the multiple collections based storage scheme for maintaining persistently SDEs with a XML DBMS Xindice. To provide efficient aggregating service for service data elements, which is running under wide area environment like Internet, the aggregator service is asynchronously operated by notification mechanism.

• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.99-106
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• 2004

This paper describes main characteristics of Grid Services based on OGSA and a service component for aggregating service data element. In order to build a Grid Service for SOA, it needs to consider a systematic approach from the high-level software architecture of a system that describes the main system components and their interactions. The purpose of this paper is to design and implement an extended service data aggregator service. To provide reliable aggregating service for service data elements, which is running under wide area environment like Internet, the aggregator service is operated asynchronously by notification mechanism.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.83-90
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• 2016

The emergence of cloud has been able to provide a variety of IT service to the user. As organizations and companies are increased that provide these cloud service, many problems arises on integration. However, with the advent of latest technologies such as big data, document-oriented database, and MapReduce, this problem can be easily solved. This paper is intended to design the Cloud Aggregator to provide them as a service to collect information of the cloud system providing each service. To do this, we use the DBaaS(DataBase as a Service) and MapReduce techniques. This makes it possible to maintain the functionality of existing system and correct the problem that may occur depending on the combination.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.832-835
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• 2008

PubMed stands alone among database related to biomedical literature. On this thesis, PubMed meta-data at some point is collected and built. The service model which serve the dynamic RSS channel, one of the core services in an web2.0 era, is designed and developed. E-Utilities service(API) served by PubMed are analyzed. The meta-data aggregator and builder are developed. Also the dynamic RSS channel generator is developed and the method how it could be used in the RSS reader is suggested.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.318-327
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• 2008

With the advance of information technologies and the spread of Internet use, the volume of usable information is increasing explosively. A content recommendation system provides the services of filtering out information that users do not want and recommending useful information. Existing recommendation systems analyze the records and patterns of Web connection and information demanded by users through data mining techniques and provide contents from the service provider's viewpoint. Because it is hard to express information on the users' side such as users' preference and lifestyle, only limited services can be provided. The semantic Web technology can define meaningful relations among data so that information can be collected, processed and applied according to purpose for all objects including images and documents. The present study proposes a content recommendation search system that can update and reflect personalized profiles dynamically in semantic Web environment. A personalized profile is composed of Collector that contains the characteristics of the profile, Aggregator that collects profile data from various collectors, and Resolver that interprets profile collectors specific to profile characteristic. The personalized module helps the content recommendation server make regular synchronization with the personalized profile. Choosing music as a recommended content, we conduct an experience on whether the personalized profile delivers the content to the content recommendation server according to a service scenario and the server provides a recommendation list reflecting the user's preference and lifestyle.