• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.93-112
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• 2009

Recently in the area of the information environment, there are lively discussions about search 2.0 which is representative of the next generation search services. In this study, we divide information search model into matching and linking models according the developmental stages. Therefore, on the one hand, we analyze the background, main concepts, related attributes and cases of the next generation search services and the other, we identify the representative keywords by the group analysis of various attributes and cases of it. The result shows that the main keywords such as social search, artificial intelligence and semantic search, and relation/network based search are representative of the search 2.0.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.57-65
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• 2019

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.3
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• pp.502-511
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• 1996

While much research on brand loyalty have been conducted until now, little has been challenged to integrate the results of previous (studies and how the brand loyalty is developed. The purpose of this study was to) suggest and test the model of clothing brand loyalty formation via consideration of all related variables simultaneously using the LISREL. The subjects were 505 male and female college graduates or higher white collar workers in their twenties and thirties living in Seoul, Korea. The data were collected by self- administered questionnaires. The results showed that consumer knowledge, product involvement, and perceived risk are positively related to information search. However, the influence of perceived risk on information search is statistically insignificant. Product involvement is also positively related to consumer satisfaction. Information search and consumer satisfaction are positively related to brand loyalty, respectively. In conclusion, consumer knowledge, product involvement, and perceived risk have positive influences on brand loyalty through the mediating variables of information search and consumer satisfaction.

• Journal of the Ergonomics Society of Korea
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• v.23 no.3
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• pp.73-88
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• 2004

This study was contrived Hierarchical Information Search (HIS) model. HIS model is based on a “cognitive process” in which model, comprising basic human information processing mechanize and information interaction. Its process include 3 semantic cognitive processes: Schema-Association LTM, Form Domain, and Alternative Selection. Design methodology consists to elicitate memory, thinking and cognitive response variables. In case study, menu structure of mobile phone was applied. In result, a correlation between predictive error rate and real error rate was .892. and a correlation between selective and real reaction time was .697. This present to suggest a model of how the methodology could be applied to real system design effectively when this was used. HIS model could become one of the most important factors for success of product design. In the perspective, the systemic methodology would contribute to design a quantitative and predictive system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.

• Journal of Korean Library and Information Science Society
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• v.49 no.2
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• pp.221-244
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• 2018

This study intends to implement an OPAC prototype based on FRBR(Functional Requirements for Bibliographic Records) model, which are reflected the users' information needs and search behavior. To the end, this study applies prototyping techniques that design, evaluate and improve an early sample model. Included in this study are as follows: (1) design a conceptual model of new OPACs based on the users' information needs about FRBR-based search services, (2) implement a FRBR-based prototype with WordPress 4.2 version, (3) evaluate the FRBR-based prototype from the viewpoint of users and experts(catalogers and professors). 50 college students and 6 experts participate in the final evaluation process.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.41-56
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• 2014

The necessity of the raw data management and reuse is issued by diffusion of the recognition that research data is a national asset. In this paper, a metadata design model by schema class inheritance and a metadata integrated search model by schema objects are suggested for a structural management of the data. A data architecture in which an schema object has an 1 : 1 relation to the data collection was designed. A suggested model was testified by creation of a virtual schema class and objects which inherit the schema class. It showed the possibility of implement systematically. A suggested model can be used to manage the data which are produced by government agencies because schema inheritance and integrated search model present way to overcome the weak points of the 'Top-dow Hierarchy model' which is being used to design the metadata schema.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.133-141
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• 2001

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However is we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set. eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case, set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.215-221
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• 2003

Generally, we want to be searched the newest as well as some appropriate personalized information from the internet resources. However, it is a complex and repeated procedure to search some appropriate information. Moreover, because the user's interests are changed as time goes, the real time modeling of a user's interests should be necessary. In this paper, I propose PREA system that can search and filter documents that users are interested from the World Wide Web. And then it constructs the user's interest model by a modified spreading neural network. Based on this network, PREA can easily produce some queries to search web documents, and it ranks them. The conventional spreading neural network does not have a visualization function, so that the users could not know how to be configured his or her interest model by the network. To solve this problem, PREA gives a visualization function being shown how to be made his interest user model to many users.

• The Journal of Korean Medicine
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• v.35 no.1
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• pp.41-49
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• 2014

Objectives: We propose a method to model and represent formulas in Korean medicine information systems. Methods: All the formulas were codified in the form of graphs representing the relationship between a formula and its constituents. To identify a unique formula in a graph, the formula's name, the book in which the formula was written, the book where the formula was extracted, and the page number in the extracted book are used. All the formulas and the relationship between formulas are modelled as an ontology based on graphs. Results: A formula search system was constructed using our ontology, which can represent formula information efficiently by grouping and filtering of formulas. Our formula model was also constructed as a mobile application. Conclusions: The information in our formula search system depends on our ontology. However, our model or our search scenarios could be extended according to formula information.