• Journal of Korean Library and Information Science Society
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• v.18
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• pp.245-268
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• 1991

Some conclusions derived from the study are as follows : 1) Most conventional information retrieval systems require users do precisely that specify the information they require, but user's information needs are not always precise. 2) Information need arise from when users are in an anomalous stats of knowledge about some problem, so user's information needs are not always precise. 3) Information retrieval systems must assist to users make themselves correct, complement, and specify their information need. When information need arise, systems should understand the state of knowledge and will be design to present and specify their ill-defined potential information need. 4) Existing information retrieval techniques need a tool to complement current its disadvantages and to enhance retrieval efficiency. Browsing searching will be a role such as a tool. 5) Browsing searching can understand user's state of knowledge and assist to specify not only pre-searching information need but also changed information need during searching progress.

• International Journal of Knowledge Content Development & Technology
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• v.6 no.2
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• pp.29-42
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• 2016

Performing an online health search is a popular activity conducted on the Internet. Research studies from developed countries provide information on source used, type of search performed and devices used to perform the search. However, the same cannot be said about the online health information searching scene in South East Asia. Online health information searching is gaining popularity in South East Asia. Citizens in these countries are turning to the Internet to obtain health information quickly. Current research studies pertaining to online health information searching in South East Asian is limited, particularly relating to search experiences of South East Asian health searchers. Search experience is pertinent as it could deter or encourage the possibility of conducting future health searches. In this research study, a user study was conducted to describe the online search experience of South East Asian health searchers. A face to face interview with 50 participants was conducted. The interview was audio recorded and transcribed verbatim. Results indicate participants have positive and negative search experiences. In some cases, post search outcomes influenced the search experience. Results of this research study contribute to the growing domain of knowledge in relation to online health information searching. Results of this study also provide an understanding pertaining to the search experience of South East Asian online health searchers.

• The Research Journal of the Costume Culture
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• v.5 no.1
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• pp.137-150
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• 1997

This study examined the effects of demographic characteristics (education, income level) on the relationships among knowledge of textile fibers, information searching behavior on textile fabrics, and information sources of textile materials in children's clothings. The subjects were 307 mothers with preschool children(4∼6years) in Seoul. Data were collected using a self-administered questionnaire and analyzed using T-test analysis of variance, corelations, and crosstabulation analysis. The results indicated that : (1) Educational levels of consumers had significant influences on knowledge of textile fibers, information searching behavior on textile fabric, and information sources of textile materials in children's clothings. (2) There were significant relationship between consumer's knowledge of textile fibers and information searching behavior on textile materials in children's clothings.

• Korean Institute of Interior Design Journal
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• no.7
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• pp.70-78
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• 1996

Artificial Intelligence is generally concerned with tasks whose execution appears to involve some intelligence if done by humans, and knowledge-based system ( in other word, expert system) is the research about the specific domain. This concept also can be applied to interior design field. So the purpose of this study is in reconstructing the accomplishment of artificial Intelligence and knowledge engineering, searching basic theories and cased to knowledge engineering , searching basic theories and cases to formulate knowledge -based design system, and testing the posibilities how the design information can be dealt in computer system. Given that recognition , two major problems must be solved before knowledge-based CAD systems could be come practical : Firstly , identification of the interior of designers use .Secondly , representing this knowledge in a computationally effective manner. I had discussed the basic concepts on which to base a knowledge- based design model, knowledge representation schemes, and problem solving, I could find the possibility which the knowledge-based system can be applied to the interior design according to this study. But there are non-deductive, often irrational and now easily computerized design process in interior design. Those are problems which are relevant to the machine learning and the creativity in design. So there should be a lot of research about the machine learning and the creatively in design in order to construct successfully intelligent knowledge-based design system.

• The Korean Journal of Community Living Science
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• v.17 no.4
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• pp.15-27
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• 2006

Most countries recognize traditional knowledge as an economical resource in recent years, and so are actively participating in WIPO discussions for making sure of their intellectual property rights. In this study, the definition of traditional knowledge was discussed for making clear its categories and relative subjects. A tool for Korean Traditional Knowledge Resource Classification(KTKRC) was developed for putting the data of the resources in order, and was indispensable for searching for and examining cultural artifacts within the system of international intellectual property rights. KTKRC covers comprehensively our various traditional knowledge resources and has a similar structure to IPC for international searching, examining, and information exchange. KTKRC consists of a section of traditional knowledge(A), and three subsections: production technology(A0), living technology(A2) and creative technology(A4). The subsections include 8 classes, 28 subclasses, 105 groups, and a great number of subgroups.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.4
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• pp.71-84
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• 2017

The paper discusses the nature of Knowledge Organization Systems (KOSs) and shows how these can support digital library users. It demonstrates processes related to integration of KOS like the Dewey Decimal Classification, $22^{nd}$ edition (DDC22) in DSpace software (http://www.dspace.org/) for organizing and retrieving (browsing and searching) scholarly objects. An attempt has been made to use the DDC22 available in Bengali language and highlights the required mechanisms for system-level integration. It may help a repository administrator to build an IDR (Institutional Digital Repository) integrated with SKOS-enabled multilingual subject access systems for supporting subject descriptors based indexing (DC.Subject metadata element), structured navigation (browsing) and efficient searching.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1566-1574
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• 2008

Researches of current information searching focus on providing personalized results as well as matching needed queries in an enormous amount of information. This paper aims at discovering hidden knowledge to provide personalized and inferred search results based on the ontology with categorized concepts and relations among data. The current searching occasionally presents too much redundant information or offers no matching results from large volumes of data. To lessen this disadvantages in the information searching, we propose an inference algorithm that supports associated and inferred searching through the Jess engine based on the OWL ontology constraints and knowledge expressed by SWRL with association rules. After constructing the personalized preference ontology for domains such as restaurants, gas stations, bakeries, and so on, it shows that new knowledge information generated from the ontology and the rules is provided with an example of the domain of gas stations.

• International Journal of Safety
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• v.4 no.2
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• pp.12-17
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• 2005

This paper aims at the development of an knowledge base for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The knowledge base consists of a case base which contains information from the past fires and a rule base with rules from expertise. To implement the knowledge base, Access 2000, one of DB development tools under windows environment and Visual Basic 6.0 are used as a DB building tool. For the reasoning technique, a mixed reasoning approach of a case based inference and a rule based inference has been adopted. Knowledge-based reasoning could present the cause of a newly occurred fire to be diagnosed by searching the knowledge base for reasonable matching. The knowledge-based database has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene), but also more improved diagnosis functions which can be easily wed for the electrical fire cause diagnosis system.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.19-38
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• 2014

This study focused on the role of active knowledge seeking (knowledge browsing and knowledge searching) in the context of virtual community of interest. Knowledge seeking is rarely studied as an antecedent in knowledge management (KM) research. Active knowledge seeking is considered as antecedents of sense of virtual community which mediates to knowledge sharing intention and virtual community promotion. Research hypotheses are tested by applying structure equation modeling with survey data from virtual community members in South Korea. Active knowledge seeking behavior was found to be the strong predictor of sense of virtual community, which, in turn, positively affects knowledge sharing intention and virtual community promotion. Implication to practitioners is to understand and accommodate the members' knowledge seeking efforts, who are potential contributors and promoters of the virtual community. Knowledge seeking, knowledge sharing and promoting virtual community are more of human activities than technology and this study extends the understanding of such human activities. By providing a mechanism of how knowledge seeking and sharing could work harmoniously, a virtuous circle with win-win situation could be achieved in virtual communities.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.