• Language and Information
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• v.9 no.1
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• pp.19-34
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• 2005

Ontology is an indispensable component in intelligent and semantic processing of knowledge and information, such as in semantic web. However, ontology construction requires vast amount of data collection and arduous efforts in processing these un-structured data. This study proposed a methodology to automatically construct and generate ontologies from Sejong Electronic Dictionary. As Sejong Electronic Dictionary is structured in XML format, it can be processed automatically by computer programmed tools into an OWL(Web Ontology Language)-based ontologies as specified in W3C . This paper presents the process and concrete application of this methodology.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.189-192
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• 2007

This study proposes a Natural Language Query Framework (NLQF) on the semantic web to support the intelligent deduction at semantic level. A large number of former researches are focused on the knowledge representation on the semantic web. However, to revitalize the intelligent agent (IA)-based automated e-business contract with human customers, there is a need for semantic level approach to the web information. To enable accessing web information at semantic level, this paper discusses the pattern of complex natural language processing at first, and then the semantic web-based natural language inference in e-business environment. The NL-based approach could help the IAs on the web to communicate with customers and other IAs with more natural interface than traditional HTML-based web information. Therefore, our proposed NLQF will be used in semantic web-based intelligent e-business contracts between customers and IAs.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.451-457
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• 2005

In spite of the development of computers, the present state that a lot of electronic documents are overflowing makes it more difficult for us to get appropriate information. Therefore, it's more important to focus on getting meaningful information than processing the data quickly In this context, Semantic Web enables an intelligent processing by adding semantic metadata on yow web documents. Also, as the Semantic Web grows, the knowledge resources as well as web resources are getting more and more importance. In this paper, we propose an OWL storage system aiming at an intelligent Processing by adding semantic metadata on your web documents, plus a system aiming at an OWL-QL Query Processing.

• Spatial Information Research
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• v.18 no.5
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• pp.83-92
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• 2010

Recently, as the Geospatial Web is combined with the Semantic Web in order to keep pace with the recent trends of information technology emphasizing interoperability, intelligence and individualization, the Geo Semantic Web was proposed, which is an intelligent geographical information Web service technology that can provide users with suitable information by connecting and integrating various types of spatial information and extensive aspatial information on the Web efficiently. For the Geo Semantic Web service, we need to develop Geo Ontology processing technologies that enable computers to process knowledge and information scattered around in the Web environment automatically. However, standards for Geo Ontology processing technologies have nod been established yet, and standardization organizations and various groups and agencies are conducting relevant studies. This paper analyzed various base theories and technologies related to Geo Ontology and developed a Geo Semantic Web system. The Geo Semantic Web system comprises Query Processing Manager that analyzes and processes Geo Semantic queries and manages sessions, Ontology Manager that generates and queries Geo Ontology and extracts spatial/aspatial data, and Clients. Finally, this paper proved the utility of the Geo Semantic Web system by applying it to a hypothetical scenario where Geo Semantic queries are required.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.113-130
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• 2010

During the decades, considerable human interventions to comprehend the web information were increased continually. The successful expansion of the web services made it more complex and required more contributions of the users. Many researchers have tried to improve the comprehension ability of computers in supporting an intelligent web service. One reasonable approach is enriching the information with machine understandable semantics. They applied ontology design, intelligent reasoning and other logical representation schemes to design an infrastructure of the semantic web. For the features, the semantic web is considered as an intelligent access to understanding, transforming, storing, retrieving, and processing the information gathered from heterogeneous, distributed web resources. The goal of this study is firstly to explore the problems that restrict the applications of web services and the basic concepts, languages, and tools of the semantic web. Then we highlight some of the researches, solutions, and projects that have attempted to combine the semantic web and business support, and find out the pros and cons of the approaches. Through the study, we were able to know that the semantic web technology is trying to offer a new and higher level of web service to the online users. The services are overcoming the limitations of traditional web technologies/services. In traditional web services, too much human interventions were needed to seek and interpret the information. The semantic web service, however, is based on machine-understandable semantics and knowledge representation. Therefore, most of information processing activities will be executed by computers. The main elements required to develop a semantic web-based business support are business logics, ontologies, ontology languages, intelligent agents, applications, and etc. In using/managing the infrastructure of the semantic web services, software developers, service consumers, and service providers are the main representatives. Some researchers integrated those technologies, languages, tools, mechanisms, and applications into a semantic web services framework. Therefore, future directions of the semantic web-based business support should be start over from the infrastructure.

• 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 Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.88-98
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• 2000

Cooperative query answering provides neighborhood or associate information relevant to the initial query using the knowledge about the query and data. In this paper, we present an intelligent query answering system for suporting cooperative query answering system presented in this paper performs query relaxation process using hybrid knowledge base. The hybrid knowledge base which is used for relaxation of queries, composes of semantic list and rule based knowledge base for structural approach. Futhermore, this paper proposes the query relaxation algorithm for query reformulation using initial query on the basis of hybrid knowledge base.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.122-129
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• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.285-291
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• 2001

This paper describes a natural language question answering system that can be used by students in getting as solution to their queries. Unlike AI question answering system that focus on the generation of new answers, the present system retrieves existing ones from question-answer files. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, it uses a semantic knowledge base (WordNet) to improve its ability to match question. Paper describes the design and the current implementation of the system as an intelligent tutoring system. Main drawback of the existing tutoring systems is that the computer poses a question to the students and guides them in reaching the solution to the problem. In the present approach, a student asks any question related to the topic and gets a suitable reply. Based on his query, he can either get a direct answer to his question or a set of questions (to a maximum of 3 or 4) which bear the greatest resemblance to the user input. We further analyze-application fields for such kind of a system and discuss the scope for future research in this area.