• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.55-60
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• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.95-106
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• 2017

Interest in companion screen services and high-definition television broadcasting services are rising along with the advanced of digital broadcasting communication technology. Not only providing good-quality broadcasting services in the main screen, but also creating added values of companion services in the secondary screen are important. In this paper we suggest a platform and a related authoring tool generating adaptive companion screen services according to user contexts. The Platform providing adaptive companion screen services based on user environment is designed and implemented for real service market. Proposed platform organizes a higher quality content service considering both user contexts and demands of service providers in real time, and the related authoring tool enables a novice user interface designer and service director to make adaptive user interfaces quickly and easily. We developed and simulated this platform in accordance with Korean UHD IBB standard which provides interactive service applications.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.460-469
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• 2006

Recently, a demand of adaptive multimedia service, which supports multimedia service migration according to user's location and characteristics of user device, is increased. In this paper, we propose a service migration system, which becomes aware of user device using intelligent agent. And we design and implement the ontology-based intelligent agent, which is aware of the context in its environment. Moreover, we implement a context reasoning system using location information.

• Journal of KIISE
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• v.44 no.5
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• pp.545-552
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• 2017

Because of the explosive growth of mobile devices and development of network technologies, HTTP (Hypertext Transfer Protocol) adaptive streaming has become a new trend in video delivery to provide efficient multimedia streaming services. As interest in personalized broadcasting grows, the study of interactive multimedia has been actively pursued. The interactive multimedia service is a method of playing media according to a scenario selected by the user. Providing the interactive multimedia service with the existing HTTP adaptive streaming causes switching delay and buffer underflow according to the point in time when the user selects the scenario while the client streams the interactive multimedia and therefore decreases the user QoE (Quality of Experience). In this paper, we propose an adaptive streaming scheme for interactive multimedia service in HTTP adaptive streaming to provide seamless playback. We design the architecture and prefetching scheme for interactive multimedia streaming.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1062-1072
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• 2006

Recently, new intelligent service frameworks, such as ubiquitous computing are proposed. So, the necessity of adaptive agent system has been increased. In this paper, we propose an intelligent service agent to help that ubiquitous computing system offer user suitable service in ubiquitous computing environment. In order to offer user suitable uT-service, an intelligent service agent mediates the gap between the context information in uT-service system, and user preference is reflected in it. Therefore, we focus on following three components; the first is suitable multi agent framework-agent communication analysis and applicable method of inference engine, the second is uT-ontologies to describe various context information-context information sharing between agents and context information understanding between agents, the third is learning method of user profile to apply in uT-service system. This approach enables us to build adaptive uT-service system to offer suitable service according to user preference.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.545-558
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• 2003

It is expected that per-user customized services are widely used in next generation Personal Communication Network. The ultimate goal for personalized service is the Virtual home Environment (VHE) providing ´same-look-and-feel´ services for the subscriber wherever he roams to. To provide personalized services for each call, per-user service profiles are frequently referenced, so efficient service profile management is essentially required. To realized the VHE, typically two schemes, can be employed; One is Intelligent Network based service control and the other is a full replication scheme that always replicates profile in user´s current zone. The first scheme is referred as Central scheme and th second scheme is the modified replication scheme of IMT-2000, we refer to as Follow-Me Replication Unconditional (FMRU). Since the Central scheme only depends on the service cal rate and the FMRU is merely dependent on the movement rate, it is apparent that FMRU scheme outperforms the Central scheme if the call to mobility ratio (CMR) is large, and vice versa. In this paper, we propose a new service profile replication schemes, Adaptive Follow-Me Replication (AFMR) that determine replication automatically according to the user´s CMR. We compared the performance of the AFMR with the non-adaptive Follow-Me Replication unconditional on Demand (FMRUD) scheme. Performance results indicate that as the CMR of a user changes AFMR adapts well compared to the existing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.784-799
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• 2013

This paper presents an adaptive rate control scheme for streaming-based content sharing service. This scheme delivers multimedia contents from a user device to another device or seamlessly redirects streaming service across heterogeneous user devices. In the proposed scheme, a streaming server adjusts video quality level according to the network and client status. Our scheme is different from other rate control schemes, because the video quality at the server is decided not only based on the available bandwidth, but also based on the device characteristics and bandwidth requirement at the access network. We also propose a bandwidth estimation method to achieve more equitable bandwidth allocations among streaming flows competing for the same narrow link with different Round Trip Times (RTTs). Through the simulation, we prove that our scheme improves the network stability and the quality of streaming service by appropriately adjusting the quality of the video stream. The simulation results also demonstrate the ability of the proposed scheme in ensuring RTT-fairness while remaining throughput efficient.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1074-1077
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• 2002

This paper proposes an adaptive pricing system with scheduling to balance the demand for contents and to realize an effective use of resources in contents delivery networks. In the proposed adaptive pricing system, the table of the service levels and prices (tariff) is shown to each user at the start of service and each user chooses one of the service classes. These prices are decided adaptively reflecting the congestion state of the networks. Then, by the proposed scheduling algorithm, these requests are scheduled so as to keep the service level agreements completely.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.257-264
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• 2012

The development of mobile devices and the spread of wireless network help share and exchange information and resources more easily. The bond them to Cloud Computing technology help pay attention to "Mobile Cloud" service, so there have been being a lot of studies on "Mobile Cloud" service. Especially, the important of 'Recommendation Service' which is customized for each user's preference and context has been increasing. In order to provide appropriate recommendation services, it enables to recognize user's current state, analyze the user's profile like user's tendency and preference, and draw the service answering the user's request. Most existing frameworks, however, are not very suitable for mobile devices because they were proposed on the web-based. And other context information except location information among user's context information are not much considered. Therefore, this paper proposed the context-aware framework, which provides more suitable services by using user's context and profile.

• ETRI Journal
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• v.27 no.1
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• pp.43-52
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• 2005

In this paper, we introduce an adaptive radio resource allocation for IP-based mobile satellite services. We also present a synchronous multibeam CDMA satellite system using an orthogonal resource sharing mechanism among downlink beams for the adaptive packet transmission. The simulation results, using a Ka-band mobile satellite channel and various packet scheduling schemes, show that the proposed system and resource allocation scheme improves the beam throughput by more than two times over conventional systems. The simulation results also show that, in multibeam satellite systems, a system-level adaptation to a user's channel and interference conditions according to user locations and current packet traffic is more efficient in terms of throughput improvement than a user-level adaptation.