• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.192-200
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• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• ETRI Journal
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• v.29 no.6
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• pp.794-807
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• 2007

In the mobile Internet, users generally work with handheld devices with limited computing power and small screens. Their access conditions also change frequently. In this paper, we present a novel method supporting intelligent content adaptation to better suit handheld devices. The underpinning is a unit of information (UOI)-based content adaptation method, which automatically detects semantic relationships among the components of Web contents and then reorganizes page layout to fit handheld devices based on identified UOIs. Experimental results demonstrate that our method enables more sensitive content adaptation.

• ETRI Journal
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• v.31 no.1
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• pp.10-20
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• 2009

In this paper, a video broadcasting system between a home-server-type device and a mobile device is proposed. The home-server-type device can automatically extract semantic information from video contents, such as news, a soccer match, and a baseball game. The indexing results are utilized to convert the original video contents to a digested or arranged format. From the mobile device, a user can make recording requests to the home-server-type devices and can then watch and navigate recorded video contents in a digested form. The novelty of this study is the actual implementation of the proposed system by combining the actual IT environment that is available with indexing algorithms. The implementation of the system is demonstrated along with experimental results of the automatic video indexing algorithms. The overall performance of the developed system is compared with existing state-of-the-art personal video recording products.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.354-360
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• 2006

The purpose of this paper is to propose a securely personalized context-aware cooperative query that supports a multi-level data abstraction hierarchy and conceptual distance metric among data values, while considering privacy concerns around user context awareness. The conceptual distance expresses a semantic similarity among data values with a quantitative measure, and thus the conceptual distance enables query results to be ranked. To show the feasibility of the methodology proposed in this paper we have implemented a prototype system in the area of site search in a large-scale shopping mall.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1050-1061
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• 2000

This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.

• Journal of Computing Science and Engineering
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• v.3 no.3
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• pp.143-164
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• 2009

This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model. In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and future trends.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.24-31
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• 2017

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.140-145
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• 2006

유비쿼터스 컴퓨팅 환경에서 사용자는 언제 어디서나 서비스를 제공받기를 원한다. 특히 멀티미디어 서비스의 경우 사용자의 위치가 변함에 따라 사용자와 가장 가까운 디스플레이를 통한 끊김없는(seamless) 멀티미디어 서비스를 요구한다. 본 논문은 이와 같이 다양한 디스플레이 디바이스를 통한 끊김없는 멀티미디어 서비스를 지원하기 위한 ADDC (Active Display Device Change) 프레임워크를 제안한다. 우리가 제안하는 프레임워크는 사용자의 위치에 따라 더 좋은 성능을 가진 최적의 디스플레이 디바이스를 검색하기 위하여 시맨틱(semantic) 서비스 디스커버리 기법을 이용하였다. 또한, 디스플레이 변경 시 능동적인 멀티미디어 세션 이동을 지원하는 핸드오프 관리자를 각 디스플레이 디바이스에 둔다. 마지막으로 디스플레이 디바이스의 특성을 고려한 멀티미디어 품질 적응(adaptation)을 위하여 트랜스코딩 서버를 이용한다. 제안한 프레임워크는 ICU에서 개발한 유비쿼터스 컴퓨팅 환경을 위한 미들웨어인 Active Surroundings를 이용하여 구현하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.519-524
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• 2010

In this paper, we will introduce our approach for composing operation based on user tasks. It is based on Service Component Architecture (SCA). In addition, we developed ontology based on OWL and the MIT process handbook, called u-TO(universal task ontology), which can be used for users describing and specifying semantically their needs. We represent the hierarchy of tasks, and classify tasks according to views in u-TO. It aims at facilitating the modeling of complex demands or systems without regarding details of technical aspects of underlying infrastructure.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1136-1140
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• 2010

Esterel is an imperative synchronous language and its formal semantic based on finite state machine makes it easy to perform program analyses using automata. In this paper, we propose a syntax-driven automata generation rule. Because our rule intuitively expresses syntactic structure, it is very useful for other program analyses.