• Title/Summary/Keyword: Semantic integrity

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Applying OWL SameAs to an Ontology in the Semantic Web (시맨틱 웹 온톨로지에서의 OWL sameAs 적용)

  • Kang, In-Su;Jung, Han-Min;Lee, Seung-Woo;Kim, Pyung;Lee, Mi-Kyung;Sung, Won-Kyung
    • Journal of KIISE:Software and Applications
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    • v.34 no.4
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    • pp.359-367
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    • 2007
  • The ontology is the underlying knowledge base to create the semantic web. Prerequisites for the success of the semantic web include widespread uses/sharing/merging of ontologies. In addition, it is very crucial to secure the integrity of ontology instances such as instance-identifying/referring integrity, and attribute domain constraints. In terms of ensuring instance-identifying integrity, OWL provides owl:sameAs property which is used to connect two separate ontology instances in order to represent that the two instances are the same. Recent semantic web works, however, have not sufficiently investigated the issues one may face in applying owl:sameAs to real semantic web applications. This study introduces our experiences of sameAs in developing a semantic web service framework for a research domain.

Development of Graph based Deep Learning methods for Enhancing the Semantic Integrity of Spaces in BIM Models (BIM 모델 내 공간의 시멘틱 무결성 검증을 위한 그래프 기반 딥러닝 모델 구축에 관한 연구)

  • Lee, Wonbok;Kim, Sihyun;Yu, Youngsu;Koo, Bonsang
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.3
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    • pp.45-55
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    • 2022
  • BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

Real-time Data Integration using Ontology and Semantic Mediators (온톨로지와 시맨틱 중재 에이전트를 이용한 실시간 통합 환경 구축에 관한 연구)

  • Park, Jin-Soo
    • Asia pacific journal of information systems
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    • v.16 no.4
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    • pp.151-178
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    • 2006
  • The objective of this research is to develop a formal framework and methodology to facilitate real-time data integration, thus enabling semantic interoperability among distributed and heterogeneous information systems. The proposed approach is based on the concepts of "ontology" and "semantic mediators." An ontology is developed and used to capture the intension (including structure, integrity rules and meta-properties) of the database schema. We also develop the agent communication protocol for semantic reconciliation, which is based on the theory of speech acts and agent communication language. This protocol is used by a set of semantic mediators, which automatically detect and resolve various semantic conflicts at the data- and schema-levels by referring to the ontology. A mediation-based query processing technique is developed to provide uniform and integrated access to the multiple heterogeneous information sources. Prototype tools are being implemented to provide proof of concept for this work.

An Algorithm for Referential Integrity Relations Extraction using Similarity Comparison of RDB (유사성 비교를 통한 RDB의 참조 무결성 관계 추출 알고리즘)

  • Kim, Jang-Won;Jeong, Dong-Won;Kim, Jin-Hyung;Baik, Doo-Kwon
    • Journal of the Korea Society for Simulation
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    • v.15 no.3
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    • pp.115-124
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    • 2006
  • XML is rapidly becoming technologies for information exchange and representation. It causes many research issues such as semantic modeling methods, security, conversion far interoperability with other models, and so on. Especially, the most important issue for its practical application is how to achieve the interoperability between XML model and relational model. Until now, many suggestions have been proposed to achieve it. However several problems still remain. Most of all, the exiting methods do not consider implicit referential integrity relations, and it causes incorrect data delivery. One method to do this has been proposed with the restriction where one semantic is defined as only one same name in a given database. In real database world, this restriction cannot provide the application and extensibility. This paper proposes a noble conversion (RDB-to-XML) algorithm based on the similarity checking technique. The key point of our method is how to find implicit referential integrity relations between different field names presenting one same semantic. To resolve it, we define an enhanced implicity referentiai integrity relations extraction algorithm based on a widely used ontology, WordNet. The proposed conversion algorithm is more practical than the previous-similar approach.

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A Proposal of Deep Learning Based Semantic Segmentation to Improve Performance of Building Information Models Classification (Semantic Segmentation 기반 딥러닝을 활용한 건축 Building Information Modeling 부재 분류성능 개선 방안)

  • Lee, Ko-Eun;Yu, Young-Su;Ha, Dae-Mok;Koo, Bon-Sang;Lee, Kwan-Hoon
    • Journal of KIBIM
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    • v.11 no.3
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    • pp.22-33
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    • 2021
  • In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.

Design and Implementation of a Spatial-Operation-Trigger for Supporting the Integrity of Meet-Spatial-Objects (상접한 공간 객체의 무결성 지원을 위한 공간 연산 트리거의 설계 및 구현)

  • Ahn, Jun-Soon;Cho, Sook-Kyoung;Chung, Bo-Hung;Lee, Jae-Dong;Bae, Hae-Young
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.2
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    • pp.127-140
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    • 2002
  • In a spatial database system, the semantic integrity should be supported for maintaining the data consistency. In the real world, spatial objects In boundary layer should always meet neighbor objects, and they cannot hold the same name. This characteristic is an implied concept in real world. So, when this characteristic is disobeyed due to the update operations of spatial objects, it is necessary to maintain the integrity of a layer. In this thesis, we propose a spatial-operation-trigger for supporting the integrity of spatial objects. The proposed method is defined a spatial-operation-trigger based on SQL-3 and executed when the constraint condition is violated. A spatial-operation-trigger have the strategy of execution. Firstly, for one layer, the spatial and aspatial data triggers are executed respectively. Secondly, the aspatial data trigger for the other layers is executed. Spatial-operation-trigger for one layer checks whether the executed operation updates only spatial data, aspatial data, or both of them, and determines the execution strategy of a spatial-operation-trigger. Finally, the aspatial data trigger for the other layers is executed. A spatial-operation-trigger is executed in three steps for the semantic integrity of the meet-property of spatial objects. And, it provides the semantic integrity of spatial objects and the convenience for users using automatic correcting operation.

Query Optimization with Knowledge Management in Relational Database (관계형 데이타베이스에서 지식관리에 의한 질의 최적화)

  • Nam, In-Gil;Lee, Doo-Han
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.5
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    • pp.634-644
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    • 1995
  • In this paper, we propose a mechanism to transform more effective and semantically equivalent queries by using appropriately represented three kinds of knowledge. Also we proposed a mechanism which transforms partially omitted components or expressions into complete queries so that users can use more simple queries. The knowledges used to transform and optimize are semantic, structural and domain knowledge. Semantic knowledge includes semantic integrity constraints and domain integrity constraints. Structural knowledge represents physical relationship between relations. And domain knowledge maintains the domain information of attributes. The proposed system optimizes to more effective queries by eliminating/adding/replacing unnecessary or redundant restrictions/joins.

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The Utilization of Metadata Elements and Content Designation for Improving Semantic Interoperability in Context of Digital Libraries (디지털 도서관의 의미적 상호운용성(Semantic Interoperability) 향상을 위한 메타데이터 요소와 활용에 관한 연구)

  • Chung, Eun-Kyung
    • Journal of the Korean Society for Library and Information Science
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    • v.42 no.1
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    • pp.193-211
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    • 2008
  • The purpose of this study is to examine semantic interoperability in terms of metadata elements and content designation in context of digital libraries. This study analyzed 78 digital libraries implemented using Greenstone application with respect to metadata elements and their content designation. Using crosswalks of digital libraries' metadata elements, and comparisons of content designation in elements. this study identifies three aspects which can impact semantic interoperability. First, there were less than 25% core metadata elements even within homogeneous information communities. Second, discrepancy exists between element names and their usage. Third, different levels were identified when assigning content to designated elements in terms of integrity and completeness.

A XML Schema Matching based on Fuzzy Similarity Measure

  • Kim, Chang-Suk;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1482-1485
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    • 2005
  • An equivalent schema matching among several different source schemas is very important for information integration or mining on the XML based World Wide Web. Finding most similar source schema corresponding mediated schema is a major bottleneck because of the arbitrary nesting property and hierarchical structures of XML DTD schemas. It is complex and both very labor intensive and error prune job. In this paper, we present the first complex matching of XML schema, i.e. XML DTD, inlining two dimensional DTD graph into flat feature values. The proposed method captures not only schematic information but also integrity constraints information of DTD to match different structured DTD. We show the integrity constraints based hierarchical schema matching is more semantic than the schema matching only to use schematic information and stored data.

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An Algorithm for Translation from RDB Schema Model to XML Schema Model Considering Implicit Referential Integrity (묵시적 참조 무결성을 고려한 관계형 스키마 모델의 XML 스키마 모델 변환 알고리즘)

  • Kim, Jin-Hyung;Jeong, Dong-Won;Baik, Doo-Kwon
    • Journal of KIISE:Databases
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    • v.33 no.5
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    • pp.526-537
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    • 2006
  • The most representative approach for efficient storing of XML data is to store XML data in relational databases. The merit of this approach is that it can easily accept the realistic status that most data are still stored in relational databases. This approach needs to convert XML data into relational data or relational data into XML data. The most important issue in the translation is to reflect structural and semantic relations of RDB to XML schema model exactly. Many studies have been done to resolve the issue, but those methods have several problems: Not cover structural semantics or just support explicit referential integrity relations. In this paper, we propose an algorithm for extracting implicit referential integrities automatically. We also design and implement the suggested algorithm, and execute comparative evaluations using translated XML documents. The proposed algorithm provides several good points such as improving semantic information extraction and conversion, securing sufficient referential integrity of the target databases, and so on. By using the suggested algorithm, we can guarantee not only explicit referential integrities but also implicit referential integrities of the initial relational schema model completely. That is, we can create more exact XML schema model through the suggested algorithm.