• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.35-45
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• 2012

Researchers and scientists spend huge amount of time in analyzing the previous studies and their results. In order to timely take the advantageous position, they usually analyze various resources such as paper, patents, and Web documents on recent research issues to preoccupy newly emerging technologies. However, it is difficult to select invest-worthy research fields out of huge corpus by using the traditional information search based on keywords and bibliographic information. In this paper, we propose a method for efficient creation, storage, and utilization of semantically relevant information among technologies, products and research agents extracted from 'big data' by using text mining. In order to implement the proposed method, we designed an ontology that creates technological knowledge for semantic web environment based on the relationships extracted by text mining techniques. The ontology was utilized for InSciTe Adaptive, a R&D trends analysis and forecast service which supports the search for the relevant technological knowledge.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.195-210
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• 2003

With the rapid development of information technology and internet in these days, resources of knowledge information have been digitalized and distributed on the internet, However, the location of digital content and a change of content have generated problems for users access and services. In line with this regard, the research on the identification of digital content utilizing standardized identification system and distribution system is necessary. This study intends to contribute to the implementation of information system based on standard digital identifier for the effective management and safe distribution of digital contents. This study first tries to survey SDI outline, practical application case and distributed business model and to analyze information distribution status Finally, this study tries to draw up a plan for the establishment of KISTI's SDI. content identification system, content distribution system.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.1
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• pp.38-48
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• 2005

ERP system is a fundamental system that is commonly adopted by most companies that intend to take part in e-business. However, few companies are running ERP systems successfully because of inaccuracy in data managed by ERP system. In this paper, we propose a model and the building process of item ontology which organize concepts describing all items managed by enterprises. In addition, we design and implement a system to create and manage item ontologies. We interface our system with a commercial ERP system, then install and run these systems on a manufacturing company. Our item ontologies and management system might help enterprises when they try to take part in e-business.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.292-298
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• 2011

In order to acquire new information and biological meaning of the signal data by defining the relationships between them, new modeling technique, ontology, has been proposed. The data of bio-signal can be represented as a systematic and logical to manage continuously bio-signal data using ontology. Furthermore, knowledge of which resources are utilized to provide improved service quality in medical information, health services in various fields. However, relevant studies have not been performed actively to compare importance of relationships between bio-signals. Therefore semantic representation of biometric information should be by defining the relationship between bio-signals. In this paper, we have developed bio-signal ontology to use as a model for using domain knowledge. We verified the usefulness of the ontology by using scenarios.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.721-729
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• 2006

Numbers of research on ontology construction and its application are being done for knowledge and information processing using computers. But, the current ontology development methods and ontology construction tools are using in restricted field on propose. Therefore, proper ontology development processes and ontology construction tools on ontology characteristic are needed. In this paper, we propose ontology construction process(OntoProcess) that non-experts in specific field are able to construct ontology through conceptualization of knowledge and formalization of concepts from language resource. Beside, some problems may be occurred while numbers of people are working together to construct ontology: i)duplicated concept definition in conceptualization process of knowledge and ii)decreasing efficiency of ontology construction by short understanding about formal language and tool operation in formalization process. To solve the problems, we propose an ontology construction process for multiple developers (OntoProcess) using meta ontology. We develop an ontology construction system(OntoCS) based on proposed processes, and we show the efficiency of proposed processes and system from ontology construction experiment.

• Journal of the Korean Society for Library and Information Science
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• v.30 no.4
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• pp.105-127
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• 1996

This paper considers the nature of a digital library in terms of definitions and its technical environment It also explores some of the problems and issues involved in demanding and supplying information So current publishing systems and the library resources were investigated. The relative advantages of both electronic and paper journals are also briefly considered and it is suggested that research relating to build the full text database is required. Finally it considers the innovative management technology such as TQM, Business Process Reengineering to innovative library itself.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.141-147
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• 2012

The purpose of the study is the acquisitions of knowledge related in job searching from local companies and job seekers using data mining techniques. At the first step, for the study, we had selected the local companies their headquarters are located in Jeonbuk province. Then we had picked the graduating students out from the high schools, colleges, and universities in the same area as the job seekers. After the targeting of the sample, we had surveyed 560 local companies and 14 schools for the collecting of the preliminary data. As the result of the survey, we could collect 173 responses from the companies and 551 responses from the job seekers. At the second step using data mining, we had adapted the C5.0 algorithm to extract the inference rules. Then we had used the Visual Basic (VB) programming language to visualize the rules at the third step. At the fourth step, we transformed the inference rules into DB tables. At the final step, we had executed the rule inferences to support the development of the long-term human resources development (HRD) strategies. As the result of the study, we could suggest the helpful information to the HRD directors and job seekers in designing their strategies in managing their jobs and career development.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.251-263
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• 2004

For question-answering system, question analysis module finds the question points from user's natural language questions, classifies the question types, and extracts some useful information for answer. This paper proposes a question type classifying technique based on focus words extracted from questions and word semantic information, instead of complicated rules or huge knowledge resources. It also shows how to find the question type without focus words, and how useful the synonym or postfix information to enhance the performance of classifying module.