• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.81-90
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• 2012

For digital TV, the recommendation of u-health personalized service of semantic environment should be done after evaluating individual physical condition, illness and health condition. The existing recommendation method of u-health personalized service of semantic environment had low user satisfaction because its recommendation was dependent on ontology for analyzing significance. We propose the personalized service recommendation method based on Naive Bayesian Classifier for u-health service of semantic environment in digital TV. In accordance with the proposed method, the condition data is inferred by using ontology, and the transaction is saved. By applying naive bayesian classifier that uses preference information, the service is provided after inferring based on user preference information and transaction formed from ontology. The service inferred based on naive bayesian classifier shows higher precision and recall ratio of the contents recommendation rather than the existing method.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.195-204
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• 2004

The Semantic Web is proposed as the next generation Web technology. In the environment of the Semantic Web, resources are related with each other semantically and computers can process this information easily. The Resource Description Framework (RDF) supports this semantic relationship. RDF is the data model for describing metadata of the Web resources. To establish and develop the Semantic Web, methods for managing RDF data efficiently are the most important. So, in this research, we propose methods for storing and querying RDF data using an XML database system. Using an XML database system, XML data, main data of the Semantic Web, and RDF data, the metadata of XML data, can be managed in the same storage and by the same mechanism efficiently. In addition, we propose an efficient data retrieval method and several techniques to improve the system performance. Our query processing technique performs better than an existing system.

• Journal of the Korea Society of Computer and Information
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• v.18 no.3
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• pp.47-57
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• 2013

Location privacy has been a serious concern for mobile users who use location-based services to acquire geographical location continuously. Spatial cloaking technique is a well-known privacy preserving method, which blurs an exact user location into a cloaked area to meet privacy requirements. However, cloaking for continuous moving object suffers from cloaked area size problem as it is unlikely for all objects travel in the same direction. In this paper, we propose a grid-based privacy preservation method with an improved Earth Mover's Distance(EMD) metric weight update scheme for semantic cloaking. We also define a representative cloaking area which protects continuous location privacy for moving users. Experimental implementation and evaluation exhibit that our proposed method renders good efficiency and scalability in cloaking processing time and area size control. We also show that our proposed method outperforms the existing method by successfully protects location privacy of continuous moving objects against various adversaries.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.1-13
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• 2009

Scene classification and concept-based procedures have been the great interest for image categorization applications for large database. Knowing the category to which scene belongs, we can filter out uninterested images when we try to search a specific scene category such as beach, mountain, forest and field from database. In this paper, we propose an adaptive segmentation method for real-world natural scene classification based on a semantic modeling. Semantic modeling stands for the classification of sub-regions into semantic concepts such as grass, water and sky. Our adaptive segmentation method utilizes the edge detection to split an image into sub-regions. Frequency of occurrences of these semantic concepts represents the information of the image and classifies it to the scene categories. K-Nearest Neighbor (k-NN) algorithm is also applied as a classifier. The empirical results demonstrate that the proposed adaptive segmentation method outperforms the Vogel and Schiele's method in terms of accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.586-593
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• 2009

As most of the data configuration at distributed environment has a tree structure following the hierarchical classification, relative data retrieve is limited. Among these data, the data stored in a database has a problem in integration and efficient retrieve. Accordingly, we suggest the system that uses XMDR for distributed database integration and links XMDR to TopicMap for efficient retrieve of knowledge expressed hierarchically. We proposes a plan for efficient integration retrieve through using the XMDR which is composed of Meta Semantic Ontology, Instance Semantic Ontology and meta location, solves data heterogeneity and metadata heterogeneity problem and integrates them, and replaces the occurrence of the TopicMap with the Meta Location of the XMDR, which expresses the resource location of TopicMap by linking Meta Semantic Ontology and Instance Semantic Ontology of XMDR to the TopicMap.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.267-273
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• 2012

The semantic relationship structures hierarchically the huge amount of document objects which is usually not formatted. However, it is very difficult to structure relevant data from various distributed application domains. This paper proposed a new object management method to service the distributed domain objects by using semantic reference relationship. The proposed mechanism utilized the profile structure in order to extract the semantic similarity from application domain objects and utilized the joint matrix to decide the semantic relationship of the extracted objects. This paper performed the simulation to show the performance of the proposed method, and simulation results show that the proposed method has better retrieval performance than the existing text mining method and information extraction method.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.655-672
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• 2003

Web services promise a new level of service on top of current web. However, in order to employ their full potential, appropriate descriptions means for web services need to be developed. Recent efforts to describe web service composition lack important features needed to enable a real automated and declarative combination of services. In this paper a set of requirements for effective Semantic Web Service composition are presented, aiming to clarify the state of the art in the area and at providing guidelines to define next steps to be accomplished. We will provide an analysis of BEPEL4WS, DAML-S and WSMF, the most important initiatives in this direction, based on these requirements, describing to what extent current efforts have developed the potential of Semantic Web Service composition.

• Journal of Korean Library and Information Science Society
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• v.37 no.3
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• pp.415-431
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• 2006

The semantic web was proposed as the next generation web technology. In the environment of the semantic web, resources as well defined and related with each other semantically, the RDF supports this basic mechanism. To establish and develop the semantic web. the basic technologies related to RDF data must be pre-established. In this research, we develop methods for storing and querying RDF data using an XML database system. As using XML database, XML data and RDF data can be integrated and efficiently managed. We construct and evaluate a system applying the proposed method to store and search data, we compared the query processing performance on our system with that of an existing system. The experiment result show that our system processes queries more efficiently.

• Annual Conference on Human and Language Technology
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• 1996.10a
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• pp.196-199
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• 1996

데이터베이스 사용자는 데이터베이스내에서 데이터를 검색하는 메카니즘과 원하는 데이터를 검색하기 위한 구체적인 질의 형태, 데이터베이스의 설계 과정에서 고려된 많은 묵시적인 의미 정보들을 인식하고 있어야 한다. 만일, 이들에 대한 정확한 인식이 이루어지지 않은채 요구된 질의는 잘못된 결과를 생성하게 된다. 데이터베이스에 대한 자연 언어 인터페이스는 이러한 세부 지식을 가지고 있지 않는 사용자에게 용이한 질의 환경을 제공해준다. 이를 위해 여러 자연 언어 인터페이스 시스템들이 개발되었다. 그러나 이 시스템들은 데이터베이스가 가지는 의미적 표현에 대한 구조적 제약성을 해소하지 못하였기 때문에 이 제약들이 사용자에게 그대로 남겨지고 있다는 문제점이 있다. 이러한 문제점은 근본적으로 자연언어와 데이터베이스의 시멘틱 모델간의 의미의 표현 레벨의 차이로 기인한다고 볼 수 있다. 본 논문은 이런 불일치 문제의 해결 방안으로 관계 데이터베이스내의 중요한 특성들을 구분하고, 이것을 표현할 수 있는 향상된 데이터베이스 시멘틱 모델에 대해 설명한다.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1540-1549
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• 2004

In this paper, we propose an algorithm to detect semantic events in golf video using Hidden Markov Model. The purpose of this paper is to identify and classify the golf events to facilitate highlight-based video indexing and summarization. In this paper we first define 4 semantic events, and then design HMM model with states made up of each event. We also use 10 multiple visual features based on MPEG-7 visual descriptors to acquire parameters of HMM for each event. Experimental results showed that the proposed algorithm provided reasonable detection performance for identifying a variety of golf events.