• Title/Summary/Keyword: semantic representation

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Building Feature Ontology for CAD System Interoperability (CAD 시스템 간의 상호 운용성을 위한 설계 특징형상의 온톨로지 구축)

  • 이윤숙;천상욱;한순흥
    • Korean Journal of Computational Design and Engineering
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    • v.9 no.2
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    • pp.167-174
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    • 2004
  • As the networks connect the world, enterprises tend to move manufacturing activities into virtual spaces. Since different applications use different data terminology, it becomes a problem to interoperate, interchange, and manage electronic data among different systems. According to RTI, approximately one billion dollar has been being spent yearly for product data exchange and interoperability. As commercial CAD systems have brought in the concept of design feature for the sake of interoperability, terminologies of design feature need to be harmonized. In order to define design feature terminology for integration, knowledge about feature definitions of different CAD systems should be considered. STEP (Standard for the Exchange of Product model data) have attempted to solve this problem, but it defines only syntactic data representation so that semantic data integration is unattainable. In this paper, we utilize the ontology concept to build a data model of design feature which can be a semantic standard of feature definitions of CAD systems. Using feature ontology, we implement an integrated virtual database and a simple system which searches and edits design features in a semantic way. This paper proposes a methodology for integrating modeling features of CAD systems.

XML-based Modeling for Semantic Retrieval of Syslog Data (Syslog 데이터의 의미론적 검색을 위한 XML 기반의 모델링)

  • Lee Seok-Joon;Shin Dong-Cheon;Park Sei-Kwon
    • The KIPS Transactions:PartD
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    • v.13D no.2 s.105
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    • pp.147-156
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    • 2006
  • Event logging plays increasingly an important role in system and network management, and syslog is a de-facto standard for logging system events. However, due to the semi-structured features of Common Log Format data most studies on log analysis focus on the frequent patterns. The extensible Markup Language can provide a nice representation scheme for structure and search of formatted data found in syslog messages. However, previous XML-formatted schemes and applications for system logging are not suitable for semantic approach such as ranking based search or similarity measurement for log data. In this paper, based on ranked keyword search techniques over XML document, we propose an XML tree structure through a new data modeling approach for syslog data. Finally, we show suitability of proposed structure for semantic retrieval.

An Application of the Semantic Web for e-Business Integration (e-비즈니스 통합을 위한 시맨틱 웹의 활용)

  • Chang Tai-Woo;Shin Kitae;Park Jinwoo
    • The Journal of Society for e-Business Studies
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    • v.10 no.4
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    • pp.19-33
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    • 2005
  • In this study, we propose a methodology of mating it easy to integrate the heterogeneous and distributed information of e-Business environments with the semantic web components , knowledge representation, ontology and agents. It is based on a collaborative interoperable environment, which should be constructed by meta-modeling and employing agents , and the syntactic/semantic integration. We adopt OWL(Web Ontology Language) to specify ontology in a layered architecture for each agent to use, which is based on the IRDS (Information Resource Dictionary Standard) framework. And we give an illustrative example using the terms from PSL(Process Specification Language)-ontology. By defining, managing and sharing resources and business-processes on the proposed framework, it could be possible to get rid of the cause of redundancy and inconsistency.

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Knowledge Representation Using Fuzzy Ontologies: A Survey

  • V.Manikandabalaji;R.Sivakumar
    • International Journal of Computer Science & Network Security
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    • v.23 no.12
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    • pp.199-203
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    • 2023
  • In recent decades, the growth of communication technology has resulted in an explosion of data-related information. Ontology perception is being used as a growing requirement to integrate data and unique functionalities. Ontologies are not only critical for transforming the traditional web into the semantic web but also for the development of intelligent applications that use semantic enrichment and machine learning to transform data into smart data. To address these unclear facts, several researchers have been focused on expanding ontologies and semantic web technologies. Due to the lack of clear-cut limitations, ontologies would not suffice to deliver uncertain information among domain ideas, conceptual formalism supplied by traditional. To deal with this ambiguity, it is suggested that fuzzy ontologies should be used. It employs Ontology to introduce fuzzy logical policies for ambiguous area concepts such as darkness, heat, thickness, creaminess, and so on in a device-readable and compatible format. This survey efforts to provide a brief and conveniently understandable study of the research directions taken in the domain of ontology to deal with fuzzy information; reconcile various definitions observed in scientific literature, and identify some of the domain's future research-challenging scenarios. This work is hoping that this evaluation can be treasured by fuzzy ontology scholars. This paper concludes by the way of reviewing present research and stating research gaps for buddy researchers.

Multilingual Knowledge Graphs: Challenges and Opportunities

  • Partha Sarathi Mandal;Sukumar Mandal
    • International Journal of Knowledge Content Development & Technology
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    • v.14 no.4
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    • pp.101-111
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    • 2024
  • Multilingual Knowledge Graphs (MKGs) have emerged as a crucial component in various natural language processing tasks, enabling efficient representation and utilization of structured knowledge across multiple languages. One can get data, information, and knowledge from various sectors, like libraries, archives, institutional repositories, etc. Variable quality of metadata, multilingualism, and semantic diversity make it a challenge to create a digital library and multilingual search facility. To accept these challenges, there is a need to design a framework to integrate various structured and unstructured data sources for integration, unification, and sharing databases. These are controlled using linked data and semantic web approaches. In future, multilingual knowledge graph overcomes all the linguistic nuances, technical barriers like semantic interoperability, data harmonization etc and enhance cooperation and collaboration throughout the world. Through a comprehensive analysis of the current state-of-the-art techniques and ongoing research efforts, this paper aims to offer insights into the future directions and potential advancements in the field of Multilingual Knowledge Graphs. This paper deals with a multilingual knowledge graph and how to build up a multilingual knowledge graph. It also focuses on the various challenges and opportunities for designing multilingual knowledge graphs.

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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Analysis and Modeling of Semantic Relationships in e-Catalog Domain (전자카탈로그에서의 의미적 관계 분석과 모델링)

  • Lee, Min-Jung;Lee, Hyun-Ja;Shim, Jun-Ho
    • The Journal of Society for e-Business Studies
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    • v.9 no.3
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    • pp.243-258
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    • 2004
  • Building a domain-suited ontology, as a means to implement the Semantic Web, is widely believed to offer users the benefit of exploiting the semantic knowledge constrained in the application. Electronic Catalog, shortly e-Catalog, manages the information about the goods or conditions play an important role in e-commerce domain. Consequently, semantically enriched yet precise information by the ontology may elaborate the business transactions. In this paper, we analyze the semantic relationships embodied within the catalog domain, as the first step towards the ontological modeling of e-catalog. Exploring ontology should leverage not only the representation of semantic knowledge but also provide the inferencing capability for the model. We employ the EER(extended Entity Relationships) for the basic model. Each modeling construct can be directly translated by DL(Description Logics). Semantic constraints that can be hardly represented in EER are directly modeled in DL.

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Genetic Clustering with Semantic Vector Expansion (의미 벡터 확장을 통한 유전자 클러스터링)

  • Song, Wei;Park, Soon-Cheol
    • The Journal of the Korea Contents Association
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    • v.9 no.3
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    • pp.1-8
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    • 2009
  • This paper proposes a new document clustering system using fuzzy logic-based genetic algorithm (GA) and semantic vector expansion technology. It has been known in many GA papers that the success depends on two factors, the diversity of the population and the capability to convergence. We use the fuzzy logic-based operators to adaptively adjust the influence between these two factors. In traditional document clustering, the most popular and straightforward approach to represent the document is vector space model (VSM). However, this approach not only leads to a high dimensional feature space, but also ignores the semantic relationships between some important words, which would affect the accuracy of clustering. In this paper we use latent semantic analysis (LSA)to expand the documents to corresponding semantic vectors conceptually, rather than the individual terms. Meanwhile, the sizes of the vectors can be reduced drastically. We test our clustering algorithm on 20 news groups and Reuter collection data sets. The results show that our method outperforms the conventional GA in various document representation environments.

Semantic-based Scene Retrieval Using Ontologies for Video Server (비디오 서버에서 온톨로지를 이용한 의미기반 장면 검색)

  • Jung, Min-Young;Park, Sung-Han
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.5
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    • pp.32-37
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    • 2008
  • To ensure access to rapidly growing video collection, video indexing is becoming more and more important. In this paper, video ontology system for retrieving a video data based on a scene unit is proposed. The proposed system creates a semantic scene as a basic unit of video retrieval, and limits a domain of retrieval through a subject of that scene. The content of semantic scene is defined using the relationship between object and event included in the key frame of shots. The semantic gap between the low level feature and the high level feature is solved through the scene ontology to ensure the semantic-based retrieval.

Auto-Analysis of Traffic Flow through Semantic Modeling of Moving Objects (움직임 객체의 의미적 모델링을 통한 차량 흐름 자동 분석)

  • Choi, Chang;Cho, Mi-Young;Choi, Jun-Ho;Choi, Dong-Jin;Kim, Pan-Koo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.36-45
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    • 2009
  • Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

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