• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.44-52
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• 2012

This paper proposes to increase an efficiency of somebody searching information by a visualization of an unseen query words with well-selected user's intent structures. If a search engine identifies user's intent to pursue information, it would be an effective search engine. To do so, it is needed that relationships between query-words are to be visible after recovering words lost during formulated, and that an intention structure/elements is to be established. This paper will review previous studies, after then, define a simple structure of the search intent, and show a process to expand and to generate the query words appropriate to the intent structure with a method for the visualization of the query words. In this process, some examples and tests are necessary that one of the multiple intent structured layers is to assign to a range of query-words. Increasing/Decreasing an efficiency are analyzed to find. Future research is needed how to automate a process to extend structural nodules of user's intent.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3699-3719
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• 2017

Conjunctive keyword search encryption is an important technique for protecting sensitive personal health records that are outsourced to cloud servers. It has been extensively employed for cloud storage, which is a convenient storage option that saves bandwidth and economizes computing resources. However, the process of searching outsourced data may facilitate the leakage of sensitive personal information. Thus, an efficient data search approach with high security is critical. The multi-user search function is critical for personal health records (PHRs). To solve these problems, this paper proposes a novel multi-user conjunctive keyword search scheme (mNCKS) without a secure channel against keyword guessing attacks for personal health records, which is referred to as a secure channel-free mNCKS (SCF-mNCKS). The security of this scheme is demonstrated using the Decisional Bilinear Diffie-Hellman (DBDH) and Decision Linear (D-Linear) assumptions in the standard model. Comparisons are performed to demonstrate the security advantages of the SCF-mNCKS scheme and show that it has more functions than other schemes in the case of analogous efficiency.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.555-576
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• 2016

In the conventional clustering algorithms, an object could be assigned to only one group. However, this is sometimes not the case in reality, there are cases where the data do not belong to one group. As against, the fuzzy clustering takes into consideration the degree of fuzzy membership of each pixel relative to different classes. In order to overcome some shortcoming with traditional clustering methods, such as slow convergence and their sensitivity to initialization values, we have used the Harmony Search algorithm. It is based on the population metaheuristic algorithm, imitating the musical improvisation process. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. We propose in this paper a new unsupervised clustering method called the Fuzzy Harmony Search-Fourier Transform (FHS-FT). It is based on hybridization fuzzy clustering and the harmony search algorithm to increase its exploitation process and to further improve the generated solution, while the Fourier transform to increase the size of the image's data. The results show that the proposed method is able to provide viable solutions as compared to previous work.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.353-359
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• 2013

The search method that web services offers has its limitations. The search service considers only functional factors based on the client's preferences. In order to improve the web service search - which alone only considers functional factors - our research introduces an execution phase which performs both functional and non-functional factors by utilizing WSDL and matching information. Our research studies the architecture of both the service selecting method and the selecting process to help determine the best service solution for the client. We do so, taking into consideration the client's preferences. Our research also studies selecting methods for the best overall service. This service not only considers the matching of functional factors provided by the web service's selecting process, but it is also accommodating by matching the information as defined by the client. This paper research can offer the best quality service preferred by any end-user. Again, this is done by utilizing web services that considers the user's non-functional factors identified by the web service's selecting process and also by extracting matching information.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.5-23
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• 2014

This study reports the first step in the Classification-based Search and Knowledge Discovery (CSKD) project, which aims to combine information organization and retrieval approaches for building digital library applications. In this study, we explored the generation and application of a faceted vocabulary as a potential mechanism to enhance knowledge discovery. The faceted vocabulary construction process revealed some heuristics that can be refined in follow-up studies to further automate the creation of faceted classification structure, while our concept search application demonstrated the utility and potential of integrating classification-based approach with retrieval-based approach. Integration of text- and classification-based methods as outlined in this paper combines the strengths of two vastly different approaches to information discovery by constructing and utilizing a flexible information organization scheme from an existing classification structure.

• 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 Society for information Management
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• v.29 no.4
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• pp.101-121
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• 2012

Since IR systems which adopt only Boolean IR model can not provide ranked search result, users have to conduct time-consuming checking process for huge result sets one by one. This study proposes a method to provide search results ranked by using coupling information between tags instead of index weight information in Boolean IR model. Because document queries are used instead of general user queries in the proposed method, key tags used as queries in a relevant document are extracted. A variety of groups of Boolean queries based on tag couplings are created in the process of extracting queries. Ranked search result can be extracted through the process of matching conducted with differential information among the query groups and tag significance information. To prove the usability of the proposed method, the experiment was conducted to find research trend analysis information on selected research information. Aslo, the service based on the proposed methods was provided to get user feedback for a year. The result showed high user satisfaction.

• Spatial Information Research
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• v.21 no.4
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• pp.7-14
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• 2013

Recently, R&D(Research and Development) is processing actively on range search in the road network environments. However, the existing representative range search techniques have shortcomings in that the greater the number of POI's, the more increased storage space or the more increased search time due to inefficient search process. Accordingly, In this paper, we proposed a range search technique using QRMP(QR-tree using Middle Point) to solve the problems of conventional range search techniques. In addition, we made a formula to obtain the total size of the storage space for QRMP and proved the excellence of the range search technique proposed in this paper through the experiment using actual road networks and POI data.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.7-22
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• 2015

This paper describes a Web search optimization study that investigates both static and dynamic tuning methods for optimizing system performance. We extended the conventional fusion approach by introducing the "dynamic tuning" process with which to optimize the fusion formula that combines the contributions of diverse sources of evidence on the Web. By engaging in iterative dynamic tuning process, where we successively fine-tuned the fusion parameters based on the cognitive analysis of immediate system feedback, we were able to significantly increase the retrieval performance. Our results show that exploiting the richness of Web search environment by combining multiple sources of evidence is an effective strategy.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.169-175
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• 2001

It is not easy for business workers to find proper information for his job, because of the following problems:(1) information exist in various information system both internal and external with diverse formats(2) he cannot estimate relevance of all the information and (3) he cannot select proper information among large volume of information. The requirements for the systems are the following things:(1) search of relevant information from various internal and external information systems(2) proving an integrated view of information for workers, and (3) information processing and decision-making are seamlessly integrated fro business workers. We proposed an agent system to fulfill the requirements. We focus on the purchasing job, and developed a prototype system. PIPA(Purchasing Information Process Agent). The PIPA performs not only information processing jobs(information search gathering, display, business form -making)but also decision-making support job (evaluation of supplier candidates, and apply of sourcing policy) for sourcing manager. The framework of the PIPA can be appled to other information processing and desision-making jobs.