• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• Journal of the Korean Home Economics Association
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• v.48 no.9
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• pp.41-54
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• 2010

This study attempted to determine how the subjective knowledge related to a consumer's life cycle influences their information search in the decision making process. The data was collected using a total of 349 questionnaires for the final analysis of this study. SPSS 12.0 for windows was used for the data analysis and the detailed analyses included descriptive analysis, factor analysis, reliability tests, one way ANOVA, multiple regression analysis and t-tests. The results of this study showed that there are differences in the subdivisions of subjective knowledge of apparel according to the consumer's life cycle and there is a difference in the types of information searches according to the consumer's subjective knowledge, and the subdivisions of subjective knowledge of the consumers influence their information search. This study showed that although it affected the internal search, the media search, and the store search, it did not influence the personal search in the decision making process.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.67-84
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• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.249-274
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• 1998

It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

• Knowledge Management Research
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• v.16 no.1
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• pp.243-254
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• 2015

To increase their market shares and grow continuously, it is very important for small and medium-sized enterprises (SMEs) to expand their markets. Although various factors may influence an SME's effort to cultivate a new market, this research focused on activities related to the search and utilization of external knowledge. After conducting Tobit analysis based on the dataset of 959 Korean SMEs included in the 2010 Korean Innovation Survey, we found that external knowledge search and utilization activities positively affect the market expansion of SMEs. This result has two implications: (1) SMEs should actively search for appropriate external knowledge sources with which they can expand their markets and reduce their dependence on internal R&D activities; and (2) they should implement an efficient corporate system to effectively absorb and utilize external knowledge inside the firms. Despite these contributions, this research has its shortcoming in that it utilized a cross-sectional dataset, which can be further analyzed by incorporating the dataset from previous and future periods.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.93-102
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• 2018

This study suggests external knowledge search as a way of creating knowledge and efforts for reaching out to the innovation and examines the relationship between innovation speed and the breadth and depth of external knowledge search. As a part of efforts to overcome the limitations of the routines of external knowledge search in the domestic market, the efforts of a firm to enter the foreign market have been examined with a moderate effect. Although previous research focused on exploration of external knowledge that is mostly effected in single country or similar industry, this study expands it by introducing the concept of market expansion and empirically inspect the interaction effect. 818 valid samples used in this study are based on the innovation survey published by STEPI and empirical results are as follows. First, the breadth and depth of external knowledge search have a positive impact on innovation speed. Second, export performance as the effect of expanding the market has a moderating effect on the speed of innovation. Third, younger companies prefer various networks while older companies prefer depth networks in order to increase the speed.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.493-513
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• 2014

With the development of related technologies, Location-Based Services (LBS) are growing fast and being used in many ways. Past LBS studies have focused on adoption of LBS because of the fact that LBS users have privacy concerns regarding revealing their location information. Meanwhile, the number of LBS users and revenues from LBS are growing rapidly because users can get some benefits by revealing their location information. Little research has been done on how LBS affects consumers' information search behavior in product purchase. The purpose of this paper is examining the effect of LBS information filtering on buyers' uncertainty and their information search behavior. When consumers purchase a product, they try to reduce uncertainty by searching information. Generally, there are two types of uncertainties - knowledge uncertainty and choice uncertainty. Knowledge uncertainty refers to the lack of information on what kinds of alternatives are available in the market and/or their important attributes. Therefore, consumers having knowledge uncertainty will have difficulties in identifying what alternatives exist in the market to fulfil their needs. Choice uncertainty refers to the lack of information about consumers' own preferences and which alternative will fit in their needs. Therefore, consumers with choice uncertainty have difficulties selecting best product among available alternatives.. According to economics of information theory, consumers narrow the scope of information search when knowledge uncertainty is high. It is because consumers' information search cost is high when their knowledge uncertainty is high. If people do not know available alternatives and their attributes, it takes time and cognitive efforts for them to acquire information about available alternatives. Therefore, they will reduce search breadth. For people with high knowledge uncertainty, the information about products and their attributes is new and of high value for them. Therefore, they will conduct searches more in-depth because they have incentive to acquire more information. When people have high choice uncertainty, people tend to search information about more alternatives. It is because increased search breadth will improve their chances to find better alternative for them. On the other hand, since human's cognitive capacity is limited, the increased search breadth (more alternatives) will reduce the depth of information search for each alternative. Consumers with high choice uncertainty will spend less time and effort for each alternative because considering more alternatives will increase their utility. LBS provides users with the capability to screen alternatives based on the distance from them, which reduces information search costs. Therefore, it is expected that LBS will help users consider more alternatives even when they have high knowledge uncertainty. LBS provides distance information, which helps users choose alternatives appropriate for them. Therefore, users will perceive lower choice uncertainty when they use LBS. In order to test the hypotheses, we selected 80 students and assigned them to one of the two experiment groups. One group was asked to use LBS to search surrounding restaurants and the other group was asked to not use LBS to search nearby restaurants. The experimental tasks and measures items were validated in a pilot experiment. The final measurement items are shown in Appendix A. Each subject was asked to read one of the two scenarios - with or without LBS - and use a smartphone application to pick a restaurant. All behaviors on smartphone were recorded using a recording application. Search breadth was measured by the number of restaurants clicked by each subject. Search depths was measured by two metrics - the average number of sub-level pages each subject visited and the average time spent on each restaurant. The hypotheses were tested using SPSS and PLS. The results show that knowledge uncertainty reduces search breadth (H1a). However, there was no significant correlation between knowledge uncertainty and search depth (H1b). Choice uncertainty significantly reduces search depth (H2b), but no significant relationship was found between choice uncertainty and search breadth (H2a). LBS information filtering significantly reduces the buyers' choice uncertainty (H4) and reduces the negative relationship between knowledge uncertainty and search breadth (H3). This research provides some important implications for service providers. Service providers should use different strategies based on their service properties. For those service providers who are not well-known to consumers (high knowledge uncertainty) should encourage their customers to use LBS. This is because LBS would increase buyers' consideration sets when the knowledge uncertainty is high. Therefore, less known services have chances to be included in consumers' consideration sets with LBS. On the other hand, LBS information filtering decrease choice uncertainty and the near service providers are more likely to be selected than without LBS. Hence, service providers should analyze geographically approximate competitors' strength and try to reduce the gap so that they can have chances to be included in the consideration set.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.1-10
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• 2015

This study examines the relationships between export intensity and knowledge search activities of Korea SME manufacturers. Using 2,145 firm data from the 2011 SME Technology Statistics Survey, we focused on the nonlinear relationships of export intensity and internal and external knowledge search activities. The results show that there are U-shaped relationships between export intensity and both of internal and external knowledge search activities. Local market-oriented or global market-oriented SMEs than the middle-level of exporters have more search activities both internally and externally. This study extends our understandings on the relationships between export intensity and knowledge search activities. There are some policy implications to develop supporting programs differing in knowledge search activities according to the acceleration of export or globalization of Korean SME manufacturers.

• Knowledge Management Research
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• v.16 no.4
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• pp.1-16
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• 2015

This paper aims to explore the small and medium sized enterprises'(SMEs') technological innovation through an open innovative strategy. Researchers have identified open innovation as external search 'breadth' and 'depth'. Although an open innovation strategy is well known as an effective way for SMEs' innovation, this stream of research examines differences between pursuing breadth of external knowledge and depth of external knowledge for SEMs' innovation. The sample comprises a total of 1106 SMEs included in the Korean Innovation Survey, and logistic regression analysis and odds ratio comparison were used to evaluate the relationship between external knowledge search and innovation outcomes. The results show that both 'breadth' and 'depth' positively affect the SMEs' innovation. When SMEs are simultaneously pursuing external searching for breadth and depth, however, a negative result on innovation outcome followed because of the lack of their internal resources and capacities. Despite these contributions, we have certain limitations that can be regarded as means of future research. Even though breadth and depth are adopted to measure the way of how a firm sources the external knowledge, companies may place the different weight on each source of knowledge. And also, it is difficult to understand how the knowledge gained through external search contributes to a firm's incremental and radical innovation, respectively.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.87-100
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• 2003

In managing organizational tacit knowledge, recent researches have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise. In this paper, we propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user′s information needs. In enabling intelligent expert searches, Fuzzy Abstraction Hierarchy (FAH) framework has been adopted, through which finding experts with similar or related expertise is possible according to the subject field hierarchy defined in the system. To improve FAH, a text categorization approach called Vector Space Model is utilized. To test applicability and practicality of the proposed framework, the prototype system, "Knowledge Portal for Researchers in Science and Technology" sponsored by the Ministry of Science and Technology (MOST) of Korea, was developed.