• International Journal of Contents
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• v.4 no.2
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• pp.19-23
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• 2008

This paper presents a novel method to construct a personalized e-Learning system based on dynamic estimations of item parameters and learners' abilities, where the learning content objects are of the same intrinsic quality or homogeneously distributed and the estimations are carried out using IRT(Item Response Theory). The system dynamically connects the test and the corresponding learning procedures. Test results are directly applied to estimate examinee's ability and are used to modify the item parameters and the difficulties of learning content objects during the learning procedure is being operated. We define the learning unit 'Node' as an amount of learning objects operated so that new parameters can be re-estimated. There are various content objects in a Node and the parameters estimated at the end of current Node are directly applied to the next Node. We offer the most appropriate learning Node for a person's ability throughout the estimation processes of IRT. As a result, this scheme improves learning efficiency in web-base e-Learning environments offering the most appropriate learning objects and items to the individual students according to their estimated abilities. This scheme can be applied to any e-Learning subject having homogeneous learning objects and unidimensional test items. In order to construct the system, we present an operation scenario using the proposed system architecture with the essential databases and agents.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.332-334
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• 2015

Nowadays a disaster event such as a building on fire, an earthquake or typhoon could occur any time, and any where. In such event, a warning notification system is a vital tool to send warning notifications to at-risk people in advance and provide them useful information to escape the dangerous area. Though some systems have been proposed such as emergency alert system using android, SMS or P2P overlay network, these works mainly focus on a reliable message distribution methods. In this work, we introduce a full prototype implementation of a personalized warning notification system based on geosocial information, which generates a personalized warning message for each user and delivers the messages through email or an android application. The system consists of four main modules: a web interface, database, a knowledge-based message generator, and message distributor. An android application is also created for user to receive warning messages on their smart phone. The prototype has been demonstrated successfully with a building-on-fire scenario.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.59-66
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• 2010

We present a personalized clothing recommender system - one that mines association rules from transaction described in ontologies and infers a recommendation from the rules. The recommender system can forecast frequently changing trends of clothing using the Onto-Apriori algorithm, and it makes appropriate recommendations for each users possible through the inference marked as meta nodes. We simulates the rule generator and the inferential search engine of the system with focus on accuracy and efficiency, and our results validate the system.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.385-387
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• 2022

With the tremendous rise in popularity of the Internet and technological advancements, many news keeps generating every day from multiple sources. As a result, the information (News) on the network has been highly increasing. The critical problem is that the volume of articles or news content can be overloaded for the readers. Therefore, the people interested in reading news might find it difficult to decide which content they should choose. Recommendation systems have been known as filtering systems that assist people and give a list of suggestions based on their preferences. This paper studies a personalized news recommendation system to help users find the right, relevant content and suggest news that readers might be interested in. The proposed system aims to build a hybrid system that combines collaborative filtering with content-based filtering to make a system more effective and solve a cold-start problem. Twitter social media data will analyze and build a user's profile. Based on users' tweets, we can know users' interests and recommend personalized news articles that users would share on Twitter.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.1-146
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• 2001

The researches of science and engineering need the latest information from internet resources. But searching and filtering processes of appropriate web documents from huge internet resources are very complex as well as having some repeated procedures. In this paper, I propose a Personalized Agent System(PAS), which can filter World Wide Web Documents that the user is interested, such as papers. To do this, PAS uses a modified spreading activation neural network which 1 propose here. PAS observes the user´s local paper database to analyze, adapt and learn the user interests, and the then constructs the user-specified neural network model by the analyzed interests ...

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.655-660
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• 2005

The number of broadcasting channels and contents are increasing with the arrival of digital broadcast and various broadcasting medium. However, there is a limit on searching of the program by using conventional program guide. Therefore, personalized broadcasting service to provide the environment, that user is able to consume his/her customized broadcasting contents at anytime, is standardized by TV-Anytime Forum. Especially. the structure of data broadcasting contents have different from that of AV contents. Therefore, it is necessary to new structure of the metadata for personalized data broadcasting service and new mechanism for data flow of broadcasting system. In this paper, we introduce a method for personalized data broadcasting service using TV-Anytime metadata.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.297-304
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• 2004

TV-Anytime specification provides metadata standards for personalized broadcasting service. For personalized broadcasting service, the metadata is transmitted through the specific way to the employed broadcasting system. In an MPEG-2 environment. the metadata can be transmitted using Sections, objects within a DSM-CC Object Carousel or modules within a DSM-CC Data Carousel. In this paper, we introduce a TV-Anytime metadata delivery method within Object Carousel which is used in ATSC-ACAP and DVB-MHP, We describe an actual example of unidirectional personalized broadcasting which is implemented on an ATSC-ACAP data broadcasting receiver, where the metadata is delivered as objects within a DSM-CC Object Carousel.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.283-296
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• 2004

TV-Anytime metadata can be delivered by unidirectional or bi-directional network. In bi -directional environment, the special request of a client is sent to metadata service providers and then the providers provide the personalized metadata back to the client. In this paper. we introduce the design and implementation of a broadcasting receiver for personalized broadcasting service in bi-directional environment. We describe actual system configuration and usage examples for bi-directional personalized service. The implemented receiver provides various functions for a digital broadcasting recorder and is based on TV-Anytime specification and UDDI specification to provide the metadata service discovery.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.206-218
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• 2002

In this paper, we design and implement a system that presents a method for selecting and providing personalized services independently without unifying the existing system platform with shopping malls joined in the hub site. This system provides a mechanism for gathering information left behind by many clients visiting Web sites for analysis of customers property, vector model for selecting personalized services, and mechanism for providing them to customers who visited in a shopping mall joined to the hub site. In a position of shopping mall site, this kind of personalization system can provide target advertisement, point marketing, and point share service etc. without changing existing shopping mall's environment through wrapper web server. Hub site customers can get personalized services from many shopping mall sites with only once registration for the hub site.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.649-660
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• 2009

To deliver services suitable to user's situation in the ubiquitous environment, the researches on realizing new services by combining existing ones have been continuously increased. But, it is difficult to provide the personalized services to each user located in the ubiquitous service space where multiple users coexist. In this paper, we propose a service composition model based on user-centered service scenarios and a system for providing personalized services through finding services suitable to user's situation and combining them. The proposed system supports a simple service discovery protocol for finding services from heterogeneous smart objects with limited computing power in the ubiquitous environment. The system aggregates and stores various service scenarios and data derived from users and executes the appropriate services for users. We design and implement a prototype system for the mobile personal device.