• Title/Summary/Keyword: Semantic Data

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Video Event Detection according to Generating of Semantic Unit based on Moving Object (객체 움직임의 의미적 단위 생성을 통한 비디오 이벤트 검출)

  • Shin, Ju-Hyun;Baek, Sun-Kyoung;Kim, Pan-Koo
    • Journal of Korea Multimedia Society
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    • v.11 no.2
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    • pp.143-152
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    • 2008
  • Nowadays, many investigators are studying various methodologies concerning event expression for semantic retrieval of video data. However, most of the parts are still using annotation based retrieval that is defined into annotation of each data and content based retrieval using low-level features. So, we propose a method of creation of the motion unit and extracting event through the unit for the more semantic retrieval than existing methods. First, we classify motions by event unit. Second, we define semantic unit about classified motion of object. For using these to event extraction, we create rules that are able to match the low-level features, from which we are able to retrieve semantic event as a unit of video shot. For the evaluation of availability, we execute an experiment of extraction of semantic event in video image and get approximately 80% precision rate.

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A cross-domain access control mechanism based on model migration and semantic reasoning

  • Ming Tan;Aodi Liu;Xiaohan Wang;Siyuan Shang;Na Wang;Xuehui Du
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.6
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    • pp.1599-1618
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    • 2024
  • Access control has always been one of the effective methods to protect data security. However, in new computing environments such as big data, data resources have the characteristics of distributed cross-domain sharing, massive and dynamic. Traditional access control mechanisms are difficult to meet the security needs. This paper proposes CACM-MMSR to solve distributed cross-domain access control problem for massive resources. The method uses blockchain and smart contracts as a link between different security domains. A permission decision model migration method based on access control logs is designed. It can realize the migration of historical policy to solve the problems of access control heterogeneity among different security domains and the updating of the old and new policies in the same security domain. Meanwhile, a semantic reasoning-based permission decision method for unstructured text data is designed. It can achieve a flexible permission decision by similarity thresholding. Experimental results show that the proposed method can reduce the decision time cost of distributed access control to less than 28.7% of a single node. The permission decision model migration method has a high decision accuracy of 97.4%. The semantic reasoning-based permission decision method is optimal to other reference methods in vectorization and index time cost.

A Semantic-based Video Retrieval System using Design of Automatic Annotation Update and Categorizing (자동 주석 갱신 및 카테고라이징 기법을 이용한 의미기반 동영상 검색 시스템)

  • 김정재;이창수;이종희;전문석
    • Journal of the Korea Computer Industry Society
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    • v.5 no.2
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    • pp.203-216
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    • 2004
  • In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

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A Semantic-based Video Retrieval System Using the Automatic Indexing Agent (자동 인덱싱 에이전트를 이용한 의미기반 비디오 검색 시스템)

  • Kim Sam-Keun;Lee Jong-Hee;Yoon Sun-Hee;Lee Keun-Soo;Seo Jeong-Min
    • Journal of Korea Multimedia Society
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    • v.9 no.1
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    • pp.127-137
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    • 2006
  • In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the automatic indexing agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

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A study of the alert decision model in sensor web enablement (SWE 에서 비상 판단 모델 연구)

  • Lee, Chang-yeol
    • Journal of the Society of Disaster Information
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    • v.5 no.2
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    • pp.76-85
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    • 2009
  • SWE(Sensor Web Enablement) is the standard platform of OGC for the sensor data service. SWE is only focusing in the data transmission protocols, but supporting the semantic decision. Sensor data service is the decision service of the status whether is on normal or not. In this study, we study the semantic decision model of the sensor data. It can support the context-aware service based on the decision information.

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Deep Hashing for Semi-supervised Content Based Image Retrieval

  • Bashir, Muhammad Khawar;Saleem, Yasir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.8
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    • pp.3790-3803
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    • 2018
  • Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

Ontology Semantic Mapping based Data Integration of CAD and PDM System (온톨로지 의미 매핑 기반 CAD 및 PDM 시스템 정보 통합)

  • Lee Min-Jung;Jung Won-Cheol;Lee Jae-Hyun;Suh Hyo-Won
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.181-186
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    • 2005
  • In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'Part' and 'Item' are different word-expressions for the same meaning. In this paper, we consider sharing between CAD and PDM data. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. Serving this purpose, the semantic mapping logic and the ontology based mapper system is described in this paper. In the semantic mapping logic topic, we introduce our logic that consists of four modules: Character Matching, Instance Reasoning, definition comparing and Similarity Checking. In the ontology based mapper, we introduce the system architecture and the mapping procedure.

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SWCL Extension for Knowledge Representation of Piecewise linear Constraints on the Semantic Web (시맨틱 웹 환경에서의 부분선형 제약지식표현을 위한 SWCL의 확장)

  • Lee, Myungjin;Kim, Wooju;Kim, Hak-Jin
    • Journal of the Korean Operations Research and Management Science Society
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    • v.37 no.4
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    • pp.19-35
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    • 2012
  • The Semantic Web technology, purporting to share, to reuse and to process by machines data stored in the Web environment, incessantly evolves to help human decision making; in particular, decision making based on data, or quantitative decision making. This trend drives researchers to fill the gap with strenuous efforts between the current state of the technology and the terminus of this evolution. The Semantic Web Constraint Language (SWCL) together with SWRL is one of these endeavors to achieve the goal. This paper focuses particularly on how to express the piecewise linear form in the context of SWCL. The importance of this ingredient can be fortified by the fact that any nonlinear expression can be approximated in the piecewise linear form. This paper will also provide the information of how it will work in the decision making process through an example of the Internet shopping mall problem.

Similarity measure for P2P processing of semantic data (시맨틱웹 데이터의 P2P 처리를 위한 유사도 측정)

  • Kim, Byung Gon;Kim, Youn Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.4
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    • pp.11-20
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    • 2010
  • Ontology is important role in semantic web to construct and query semantic data. Because of dynamic characteristic of ontology, P2P environment is considered for ontology processing in web environment. For efficient processing of ontology in P2P environment, clustering of peers should be considered. When new peer is added to the network, cluster allocation problem of the new peer is important for system efficiency. For clustering of peers with similar chateristics, similarlity measure method of ontology in added peer with ontologies in other clusters is needed. In this paper, we propose similarity measure techniques of ontologies for clustering of peers. Similarity measure method in this paper considered ontology's strucural characteristics like schema, class, property. Results of experiments show that ontologies of similar topics, class, property can be allocated to the same cluster.

Grid Management System and Information System for Semantic Grid Middleware

  • Kim, Hyung-Lae;Han, Byong-John;Jeong, In-Yong;Jeong, Chang-Sung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.6
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    • pp.1080-1097
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    • 2010
  • Well organized and easy usable Grid management system is very important for executing various Grid applications and managing Grid computing environment. Moreover, information system which can support Grid management system by providing various Grid environment related information is also one of the most interesting issue in the Grid middleware system area. Effective cooperation between Grid management system and information system can make a novel Grid middleware system. Especially, service oriented architecture based Grid management system is flexible and extensible for providing various type of Grid services. Also, information system based on data mining process which comprises various different kinds of domains such as users, resources and applications can make Grid management system more precise and efficient. In this paper, we propose semantic Grid middleware system which is a combination of Grid management system and semantic information system.