• Journal of KIISE:Databases
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• v.33 no.4
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• pp.363-371
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• 2006

In spite of computer's development, the present state of a lot of electronic documents overflowed it's going to be more difficult to get appropriate information. Therefore it's more important to get meaningful information than to focus on the speed of processing. Semantic web enables and intelligent processing by adding semantic meta data on your web documents. Also as the semantic web grows, the knowledge resource is more important. In this paper, we propose a RDF storage system using relational database model aimed at intelligent processing by adding semantic meta data on your web documents, also a query processor aimed at query processing through the storage system. By using relational model, we could overcome a weakness of object or memory model.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.1-12
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• 2019

Unlike existing Open APIs, Linked Data are made as a huge intelligent base to perform high-level SPARQL queries, and it is possible to create efficiently a new content by mashuping different information from various datasets. This paper implements a responsive web application for location-based semantic search. We mashup DBpedia, a kind of Linked Data, and GoogleMap API provided by Google, and provide a semantic browser function to confirm detail information regarding retrieved objects. Our system can be used in various access environments such as PC and mobile by applying responsive web design idea. The system implemented in this paper compares functional specifications with existing systems with similar functions. The comparison results show the superiority of our system in various aspects such as using semantic, linked-based browser, and mashup function.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.65-74
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• 2012

Cloud services are used for improving business. Moreover, customer relationship management(CRM) approaches use social networking as tools to enhance services to customers. However, most cloud systems do not support the semantic structures, and because of this, vital information from social network sites is still hard to process and use for business strategy. This paper proposes a collaboration framework based on social semantic web for cloud system. The proposed framework consists of components to support social semantic web to provide an efficient collaboration system for cloud consumers and service providers. The knowledge acquisition module extracts rules from data gathered by social agents and these rules are used for collaboration and business strategy. This paper showed the implementations of processing of social network site data in the proposed semantic model and pattern extraction which was used for the virtual grouping of cloud service providers for efficient collaboration.

• The Journal of Information Systems
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• v.18 no.3
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• pp.211-229
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• 2009

Recently, trends of information technology development include offerings of service for personalization, intelligence, and convergence. The research suggested a new tour system that tourists can make their tour packages by applying Semantic Web technology. The system includes ontologies and inference rules for offering intelligent and personalized service. Our system called MYT (Make Your Tour-package) was successfully demonstrated by employing realistic scenarios. Current version of the MYT system needs manager's intervention to link and integrate automatically ontology subsystem and Web service. In further study, the MYT will be extended to the system including a component integrating automatically subsystems and a component capturing and processing context data from RFID/USN.

• Culinary science and hospitality research
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• v.23 no.4
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• pp.22-32
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• 2017

The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

• 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.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.85-101
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• 2008

The semantic web is taken as next generation standards of information exchange on the internet to overcome the limitations of the current web. To utilize the information on the semantic web, tools are required the functionality of query search and reasoning for the ontology. However, most of semantic web management tools cannot efficiently support the search for the complex query because they apply Triple-based storage structure about RDF metadata. We design the storage structure of the ontology in corresponding with the structure of ontology data and develop the search system(SMART-DLTriple) to support complex query search efficiently in this research. The performance of the system using new storage structure is evaluated to compare with the popular semantic web management systems. The proposed method and system make a contribution to enhancement of a practical ontology reasoning systems due to improved performance of the ontology search.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.155-175
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• 2003

The purpose of the study was to construct a system based on the semantic web environment's ontology by utilizing the ontology schema derived from the facet-type Art and Architecture Thesaurus(AAT). The aforementioned ontology schema is based on the Web Ontology Language(OWL), which is being widely considered the standard ontology language for the W3C-centered semantic web environment. Also, the concepts were limited to terms within AAT'S Furniture Facet, and the system was tested using the Chair concept, which is a lower-level facet that has a diverse conceptual relationship and broad vocabulary base. The ontology system is capable of searching for concepts, while controlling the search results by always providing a 'Preferred term' for synonymous terms. In addition, the system provides the user with first, a relationship between the terms centered around the inquiry, and second, related terms along with their classification properties. Also, the system is presented as and application example of the ontology system that constructs a information system that intakes an Instance value and reproduces it into a RDF file. During this process, utilization of multiple ontologies was introduced, and the stored Instance value's meta-data elements were used.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.269-274
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• 2004

Because of the rapid development of internet and Various Types. huge amount and Various types of data are available on the web there days. The tasks such as information retrieval, composition and integration are not easy on the web which contains such huge amount of data. In order to solve these problems W3C introduced Semantic Web as a next generation Web. Semantic Web guarantee the cooperation between heterogeneous Systems and improve reusability of information by providing the machine understandable Web data. In this paper. We design develop an ontology for the museum. The implemented ontology can be used as a standard ontology for the relic search in a museum.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1491-1499
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• 2011

Now a days, to make good use of tags is a general tendency when users need to upload or search some multimedia data such as images and videos on the Web. In this paper, we introduce an approach to calculate semantic importance of tags and to make re-ranking with them on tagged Web image retrieval. Generally, most photo images stored on the Web have lots of tags added with user's subjective judgements not by the importance of them. So they become the cause of precision rate decrease with simple matching of tags to a given query. Therefore, if we can select semantically important tags and employ them on the image search, the retrieval result would be enhanced. In this paper, we propose a method to make image retrieval re-ranking with the key tags which share more semantic information with a query or other tags based on Wikipedia-based semantic relatedness. With the semantic relatedness calculated by using huge on-line encyclopedia, Wikipedia, we found the superiority of our method in precision and recall rate as experimental results.