• Title/Summary/Keyword: semantic relationships

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An Extension of SWCL to Represent Logical Implication Knowledge under Semantic Web Environment (의미웹 환경에서 조건부함축 제약 지식표현을 위한 SWCL의 확장)

  • Kim, Hak-Jin
    • Journal of the Korean Operations Research and Management Science Society
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    • v.39 no.3
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    • pp.7-22
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    • 2014
  • By the publications of RDF and OWL, the Semantic Web is confirmed as a technology through which information in the Internet can be processed by machines. The focus of the Semantic Web study after then has moved to how to provide more useful information to users for their decision making beyond simple use of the structured data in ontologies. SWRL that makes logical inference possible by rules, and SWCL that formulates constraints under the Semantic Web environment are some of many efforts toward the achievement of that goal. Constraint represents a connection or a relationship between individual data in ontology. Based on SWCL, this paper tries to extend the language by adding one more type of constraint, implication constaint, in its repertoire. When users use binary variables to represent logical relationships in mathematical models, it requires and knowledge on the solver to solve the models. The use of implication constraint ease this difficulty. Its need, definition and relevant technical description is presented by the use of the optimal common attribute selection problem in product design.

A Decision Support System for Product Design Common Attribute Selection under the Semantic Web and SWCL (시맨틱 웹과 SWCL하의 제품설계 최적 공통속성 선택을 위한 의사결정 지원 시스템)

  • Kim, Hak-Jin;Youn, Sohyun
    • Journal of Information Technology Services
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    • v.13 no.2
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    • pp.133-149
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    • 2014
  • It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

A New Similarity Measure for e-Catalog Retrieval Based on Semantic Relationship (의미적 연결 관계에 기반한 전자 카탈로그 검색용 유사도 척도)

  • Seo, Kwang-Hun;Lee, Sang-Goo
    • Journal of KIISE:Databases
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    • v.34 no.6
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    • pp.554-563
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    • 2007
  • The e-Marketplace is growing rapidly and providing a more complex relationship between providers and consumers. In recent years, e-Marketplace integration or cooperation issues have become an important issue in e-Business. The e-Catalog is a key factor in e-Business, which means an e-Catalog System needs to contain more large data and requires a more efficient retrieval system. This paper focuses on designing an efficient retrieval system for very large e-Catalogs of large e-Marketplaces. For this reason, a new similarity measure for e-Catalog retrieval based on semantic relationships was proposed. Our achievement is this: first, a new e-Catalog data model based on semantic relationships was designed. Second, the model was extended by considering lexical features (Especially, focus on Korean). Third, the factors affecting similarity with the model was defined. Fourth, from the factors, we finally defined a new similarity measure, realized the system and verified it through experimentation.

An Ontology-based Semantic Blog Model for Supporting System Queries to Recommend Interest Community (관심 커뮤니티 추천을 위한 시스템 질의를 지원하는 온톨로지 기반 시맨틱 블로그 모델)

  • Yang, Kyung-Ah;Yang, Jae-Dong;Choi, Wan
    • Journal of KIISE:Software and Applications
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    • v.35 no.4
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    • pp.219-233
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    • 2008
  • This paper suggests an intelligent semantic blog model to systematically analyze and manage biogosphere with ontology as its conceptual knowledge base. In the model, the system managers may support users to easily find appropriate blog resources by tracking and analyzing various relationships between ontology - they may intelligently recommend Interest blog communities to relevant users by monitoring interaction activities in blogoshpere, dynamically grouping the communities with the ontology. To systematically specify the functionality of our model, 1) we first express the structure of blog resources in terms of objects and relationships between them and then 2) we formalize a set of operators designed to be applied to the resources. System queries are implemented by the combination of the operators.

ONTOLOGY DESIGN FOR THE EFFICIENT CUSTOMER INFORMATION RETRIEVAL

  • Gu, Mi-Sug;Hwang, Jeong-Hee;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.345-348
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    • 2005
  • Because the current web search engine estimates the similarity of documents, using the frequency of words, many documents irrespective of the user query are provided. To solve these kinds of problems, the semantic web is appearing as a future web. It is possible to provide the service based on the semantic web through ontology which specifies the knowledge in a special domain and defines the concepts of knowledge and the relationships between concepts. In this paper to search the information of potential customers for home-delivery marketing, we model the specific domain for generating the ontology. And we research how to retrieve the information, using the ontology. Therefore, in this paper, we generate the ontology to define the domain about potential customers and develop the search robot which collects the information of customers.

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RDF 지식 베이스의 자원 중요도 계산 알고리즘에 대한 연구

  • No, Sang-Gyu;Park, Hyeon-Jeong;Park, Jin-Su
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2007.05a
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    • pp.123-137
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    • 2007
  • The information space of semantic web comprised of various resources, properties, and relationships is more complex than that of WWW comprised of just documents and hyperlinks. Therefore, ranking methods in the semantic web should be modified to reflect the complexity of the information space. In this paper we propose a method of ranking query results from RDF(Resource Description Framework) knowledge bases. The ranking criterion is the importance of a resource computed based on the link structure of the RDF graph. Our method is expected to solve a few problems in the prior research including the Tightly-Knit Community Effect. We illustrate our methods using examples and discuss directions for future research.

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Implementation of SENKOV System: A Knowledge Base for Semantic Analysis (의미분석 지식베이스를 위한 SENKOV 시스템의 구현)

  • Moon, Yoo-Jin
    • Information Systems Review
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    • v.2 no.2
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    • pp.245-253
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    • 2000
  • The paper presents methodology and techniques for design and implementation of the SENKOV System based on the validation of set membership and dictionaries. And it performs verb concept classification available for establishing the selectional restriction relationships among adverbs and verbs. The paper is important in that it has made the first attempt at classifying Korean verb concepts for the semantic analysis. We select about 600 Korean verbs which are commonly used in the daily life, and implements the SENKOV System. According to results of the experiments, SENKOV has 44 top nodes and depth of average 2.35, and that it can be utilized to classify Korean verb concept for the selectional restrictions among adverbs and verbs.

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An Associative Search System for Mobile Life-log Semantic Networks based on Visualization (시각화 기반 모바일 라이프 로그 시맨틱 네트워크 연관 검색 시스템)

  • Oh, Keun-Hyun;Kim, Yong-Jun;Cho, Sung-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.727-731
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    • 2010
  • Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.

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.

Analysis of Representation Methods for Semantic Constraints to Enhance the Quality of XBRL Services (XBRL 서비스 품질 향상을 위한 의미제약 표현 방법 분석)

  • Kim, Hyoung-Do
    • The Journal of the Korea Contents Association
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    • v.8 no.8
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    • pp.274-284
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    • 2008
  • XBRL is an XML-based language, actively used for diverse business reporting applications including financial reporting. It can be flexibly applied to each application by defining concepts and their relationships existing within the application. In these business reporting processes, it is very important for senders and receivers to validate the consistency and completeness of reporting contents in the syntatic and semantic levels. The basic method is to directly represent and validate the semantic constraints using application program codes. However, the method makes it difficult to represent, change, share semantic constraints. While XML constraint languages for XML documents such as XSLT and Schemantron support explicit representation and sharing of semantic constraints, they are limited in the efficiency and effectiveness of representing XBRL semantic constraints. This paper reviews XBRL formula, actively being discussed recently for standardization, and discusses the representation capability and limitations through a case analysis, which applies XBRL formula to business documents in the area of financial reporting.