• Knowledge Management Research
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• v.10 no.2
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• pp.85-103
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• 2009

Web 2.0, characterized as openness, sharing, and participation, has enabled Internet users to easily generate a variety of contents, and to share them through Web 2.0 services. Knowledge search service (KSS) is positioning itself as one of typical Web 2.0 services. Yet, few studies have sharpened our understanding of users' knowledge sharing behavior in the KSS environment. In order to address this knowledge void, this paper attempts to explore antecedents of their usage behavior in the KSS environment. Typically, they utilize stored knowledge and share their knowledge simultaneously. Considering this characteristic, our study regards service usage intention and knowledge sharing intention as final dependent variables. This study advances a research model based on Bhattacherjee's expectation-confirmation model, which is expanded by incorporating trust belief. Because of the openness of KSS, trust belief is believed to play a critical role in forming users' service usage intention and knowledge sharing intention. Furthermore, this study examines the difference of the antecedents' effects in terms of users' gender. We collected data from 275 respondents who have experience in using KSS. PLS (partial least squares) was employed for the analysis of the data. Analysis results confirm the important role of user satisfaction and trust belief in the formation of users' service usage intention and knowledge sharing intention. More importantly, trust belief has a more salient effect on knowledge service usage intention than user satisfaction. This study also shows the moderating role of users' gender. Finally, this paper provides managerial guidance on strategic planning aimed at improving users' service usage intention and knowledge sharing intention in the KSS environment.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.316-320
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• 2005

We developed Intelligent Product Search Agent based on SWRL, and this agent can search product information with knowledge(facts and rules) on the web, implement price comparison for searched products considering delivery rates. Existing keyword based product search engines is poor at searching intent products though a user has already prefect knowledge about intent produces. Furthermore if a user has insufficient knowledge, it is impossible to implement search. Also, existing price comparison shopping mall gives users comparison service considering total price(product prices, taxes, delivery rates), this service is valid to single product and has limitations of system expansion and up-dating because of not rule base but programming base. If there is appropriate knowledge on the Semantic web and this makes product information retrieval possible, above problems can be solved clearly. In this research, we developed Intelligent Product Search Agent based on SWRL that can search product information efficiently by making agent to handle facts and rules by itself.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

• Journal of the Korean Institute of Oriental Medical Informatics
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• v.15 no.1
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• pp.1-10
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• 2009

In these days everyone search the information easily with the Internet as the rapid distribution and active usage of the Internet. The search engines were developed specially to accuracy of information retrieval. User search the information more quickly and variously with them. The search portal system will be embossed with representation and basic services. The Internet user needs the result of text, image and video, knowledge search. The keyword based search is used generally for getting result of the information retrieval and another method is category based search. This paper investigates the classification of knowledge search structure for oriental medicine in market leader of search portal system by ranking web site. As a result, each classification system is unified and there is a possibility of getting up a many confusion to the user who approaches with classification systematic search method. This treatise proposed the improved oriental medicine classification system of internet information retrieval in knowledge search area. if the service provider amends about the classification system, there will be able to guarantee the compatibility of data. Also the proper access path of the knowledge which seeks is secured to user.

• Knowledge Management Research
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• v.18 no.2
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• pp.103-127
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• 2017

This study examines the effects of failed airline services on the consumers' psychological process and their behavioral responses. Having different classifications from the previous studies, this study focuses on dividing important factors of airline services into search attributes(e.g. sale and procedure services, services concerning flight attendant, in-flight services) and experience attributes(e.g. flight services, collateral services). Using structural equation modeling, this study shows that the failure of service factors of the experience attributes provokes the feeling of disappointment with mediation effect of external attribution while the failure of service factors of search attributes provokes the feeling of regret with mediation effect of internal attribution. Finally, disappointment leads to consumers' complaint behavior while regret leads to consumers' switching behavior. Unlike previous studies, we show that when a service failure occurs, depending on each attribute, consumers feel negative emotions of disappointment or regret through different attribution processes and finally show different behavioral responses with an empirical analysis.

• International Journal of Knowledge Content Development & Technology
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• v.14 no.3
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• pp.93-113
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• 2024

This study was conducted for the purpose of deriving the existing ScienceON elements and reorganizing them to increase user convenience and utilization. Towards this end, implications were derived by analyzing the current status of the ScienceON's website, case studies and analysis of major similar institution websites, and user satisfaction surveys. Based on the derived contents, key terms were analyzed and redefined, the menu system was reorganized, and the menu names were redefined, and the menu system was reorganized to match the direction and identity of the redefined ScienceON. The study results based on such are as follows. First, the ScienceON's brand selection criteria and direction were based on service sustainability, service inclusiveness, recognition of portal characteristics, user friendliness and intuitiveness. Considering the meaning of branding, branding strategy, and selection criteria for ScienceON branding, ScienceON, Ontong ScienceON, ScienceONPlatform, science information portal, ScienceON, Mecca of science and technology information, and 5 brand names such as ScienceON were proposed. Second, to improve accessibility, usability, and satisfaction, it would be necessary to redefine current terms. Towards this end, it would be necessary to change the terminology of knowledge infrastructure search and to unify and organize the terminology. Third, in the current menu, the services provided as analysis services and curation services are organized in the beta service menu, and data such as papers, patents, reports, and trends are also serviced only through integrated search, and hence, each data type and service type classification must be improved.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.42-44
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• 2012

본 논문에서는 개인화 검색 시 사용자의 단일 프로파일이 개인의 다양한 정보 요구를 만족시키지 못하는 문제를 개선하고자, 질의어에 따라 프로파일을 조정하는 방법을 제안한다. 특히, 제안하는 방법은 북마크 데이터로부터 질의어에 관해 사용자가 중요하게 생각하는 단어들을 추출하여 프로파일을 조정하는데 활용한다. 유명 북마크 서비스인 CiteULike의 데이터를 활용한 실험에서, 제안하는 방법이 단일 프로파일에 기반한 기존의 방법보다 더 뛰어난 개인화 검색 결과를 제공함을 확인할 수 있었다.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.191-198
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• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.525-534
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• 2006

Ontology specifies the knowledge in a specific domain and defines the concepts of knowledge and the relationships between concepts. It is possible to provide the service based on the semantic web through the ontology. Therefore, to specify and define the knowledge in a specific domain, it is required to generate the ontology which conceptualizes the knowledge. Accordingly, to search the information of potential customers for home-delivery marketing of post office, we design the specific domain to generate the ontology based on the semantic web in this paper. And we propose how to retrieve the information, using the generated ontology. We implement the data search robot which collects the information based on the generated ontology. Also, we confirm that the ontology and the search robot perform the information retrieval exactly.