• International Journal of Contents
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• v.2 no.3
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• pp.1-5
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• 2006

Intelligent Content is defined as detailed information or fragment of content which contains a semantic data structure. This semantic structure makes possible to do various intelligent operations. There are wide range of content-oriented applications such as classification, retrieval, extraction, translation, presentation and question-answering. The concept of Intelligent Content is applied to various fields like MPEG and Semantic Web. In this paper, we discuss the several important researches of Intelligent Content and how to apply this conception to these fields.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.602-609
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• 2007

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system

• ETRI Journal
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• v.29 no.2
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• pp.169-178
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• 2007

With the advent of ubiquitous computing environments, it has become increasingly important for applications to take full advantage of contextual information, such as the user's location, to offer greater services to the user without any explicit requests. In this paper, we propose context-aware active services based on context-aware middleware for URC systems (CAMUS). The CAMUS is a middleware that provides context-aware applications with a development and execution methodology. Accordingly, the applications based on CAMUS respond in a timely fashion to contextual information. This paper presents the system architecture of CAMUS and illustrates the content recommendation and control service agents with the properties, operations, and tasks for context-aware active services. To evaluate CAMUS, we apply the proposed active services to a TV application domain. We implement and experiment with a TV content recommendation service agent, a control service agent, and TV tasks based on CAMUS. The implemented content recommendation service agent divides the user's preferences into common and specific models to apply other recommendations and applications easily, including the TV content recommendations.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.601-605
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• 2010

In this paper, we propose a GBL(Game Based Learning) content of intelligent tutoring capability. The objective of our GBL content is to learn the Karnaugh Map which is generally used to simplify boolean functions. Our GBL content well-motivates learners with interesting game-based scenarios and also, through an intelligent tutoring module, gives learners adaptive feedbacks such as hints and explanations while maintaining learners' contextual immersion. Additionally, we identified significant improvement in terms of learning effectiveness by analyzing the test results of two (experimental and controlled) student groups learning the Karnaugh Map.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.479-484
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• 1998

As technology in a computer hardware and software advances, efficient information retrieval from multimedia database gets highly demanded. Recently, it has been actively exploited to retrieve information based on the stored contents. However, most of the methods emphasize on the points which are far from human intuition or emotion. In order to overcome this shortcoming , this paper attempts to apply interactive genetic algorithm to content-based image retrieval. A preliminary result with subjective test shows the usefulness of this approach.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.101-115
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• 2008

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.611-618
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• 2020

In this paper, we propose a design and implementation method of speed quiz content that can be driven by a social robot capable of interacting with humans, and a method of developing an intelligent module necessary for implementation. In addition, we propose a method of implementing speed quiz content through the process of constructing a map by arranging and connecting intelligent module blocks. Recently, software education has become mandatory and interest in programming is increasing. However, programming is difficult for students without basic knowledge of programming languages to directly access, and interest in block-type programming platforms suitable for beginners is growing. The block-type programming platform used in this paper is a platform that supports immediate and intuitive programming by supporting interactions between humans and robots. In this paper, the intelligent module implemented for the speed quiz content was used by blocking it within a block-type programming platform. In order to implement the scenario of the speed quiz content proposed in this paper, we implement a total of three image-based artificial intelligence modules. In addition to the intelligent module, various functional blocks were placed to implement the speed quiz content. In this paper, we propose a method of designing a speed quiz content scenario and a method of implementing an intelligent module for speed quiz content.

• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.433-439
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• 2020

Recently, the need for IoT-based intelligent systems is increasing in various fields. In this study, we implemented the system that automatically measures the sugar content of fruits without damage to fruit's marketability using near-infrared radiation and machine learning. The spectrums were measured several times by passing a broadband near-infrared light through a fruit, and the average value for them was used as the input raw data of the machine-learned DNN(Deep Neural Network). Using this system, he sugar content value of fruits could be predicted within 5 s, and the prediction accuracy was about 93.86%. The proposed non-destructive sugar content measurement system can predict a relatively accurate sugar content value within a short period of time, so it is considered to have sufficient potential for practical use.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1407-1417
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• 2016

In this paper, we propose a multi-level content transmission mechanism for intelligent quality of service (QoS) in social networking services (SNSs). Because existing SNSs and related work send image content to a client with a single fixed mechanism, they cannot consistently support content accessibility according to different conditions of QoS factors such as network congestion and throughput. In the proposed image transmission mechanism, our communication middleware (CM) provides an SNS developer with three transmission modes so that an SNS server or client can dynamically change the quality of images if required. In each transmission mode, an SNS server can send images to a requesting client with original high quality, thumbnail quality, or send only text information. With varying qualities of downloaded images, an SNS developed on top of CM can provide users with consistent QoS for access to SNS content.

• ETRI Journal
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• v.26 no.2
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• pp.136-148
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• 2004

It is expected that an intelligent broadcasting service (IBS) will be able to provide broadcast programs based on user preference and program-associated information (metadata) in order to assist users in easy navigation of the program content being broadcast. In this way, users will be able to access program content anytime, anywhere, and in the manner they wish. This type of IBS will be a basis for future broadcasting services such as customized broadcasting or personal casting. In this paper, we introduce an agent-based multimedia broadcasting framework using the Foundation for Intelligent Physical Agents (FIPA) and MPEG-7 technologies within MPEG-21. We use a FIPA implementation called FIPA open source as a platform for exchanging user preferences and program information as FIPA messages between a server and its clients. The user preference is modeled as the User Preference description scheme in MPEG-7 multimedia description schemes. We discuss a framework structure and implementation for the IBS.