• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1049-1062
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• 2004

With the popularization of a World Wide Web (WWW), the quantity of web information has been increased. Therefore, an efficient searching system is needed to offer the exact result of diverse Information to user. Due to this reason, it is important to extract and analysis of user requirements in the distributed information environment. The conventional searching method used the only keyword for the web searching. However, the searching method proposed in this paper adds the context information of keyword for the effective searching. In addition, this searching method extracts keywords by the new keyword extraction method proposed in this paper and it executes the web searching based on a keyword mining profile generated by the extracted keywords. Unlike the conventional searching method which searched for information by a representative word, this searching method proposed in this paper is much more efficient and exact. This is because this searching method proposed in this paper is searched by the example based query included content information as well as a representative word. Moreover, this searching method makes a domain keyword list in order to perform search quietly. The domain keyword is a representative word of a special domain. The performance of the proposed algorithm is analyzed by a series of experiments to identify its various characteristic.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.212-222
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• 2022

There has been a rapid increase in the use of cloud email services. As a result, email encryption has become more commonplace as concerns about cloud privacy and security grow. Nevertheless, this increase in usage is creating the challenge of how to effectively be searching and filtering the encrypted emails. They are popular technologies of solving the issue of the encrypted emails searching through searchable public key encryption. However, the problem of encrypted email filtering remains to be solved. As a new approach to finding and filtering encrypted emails in the cloud, we propose a ciphertext-based encrypted policy attribute-based encryption scheme and keyword search procedure based on hidden policy ciphertext. This feature allows the user of searching using some encrypted emails keywords in the cloud as well as allowing the emails filter-based server toward filter the content of the encrypted emails, similar to the traditional email keyword filtering service. By utilizing composite order bilinear groups, a hidden policy system has been successfully demonstrated to be secure by our dual system encryption process. Proposed system can be used with other scenarios such as searching and filtering files as an applicable method.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.29-48
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• 2014

The recent keyword advertising does not reflect the individual customer searching pattern because it is focused on each keyword at the aggregate level. The purpose of this research is to observe processes of customer searching patterns. To be specific, individual deal-proneness is mainly concerned. This study incorporates location as a control variable. This paper examines the relationship between customers' searching patterns and probability of purchase. A customer searching session, which is the collection of sequence of keyword queries, is utilized as the unit of analysis. The degree of deal-proneness is measured using customer behavior which is revealed by customer searching keywords in the session. Deal-proneness measuring function calculates the discount of deal prone keyword leverage in accordance with customer searching order. Location searching specificity function is also calculated by the same logic. The analyzed data is narrowed down to the customer query session which has more than two keyword queries. The number of the data is 218,305 by session, which is derived from Internet advertising agency's (COMAS) advertisement managing data and the travel business advertisement revenue data from advertiser's. As a research result, there are three types of the deal-prone customer. At first, there is an unconditional active deal-proneness customer. It is the customer who has lower deal-proneness which means that he/she utilizes deal-prone keywords in the last phase. He/she starts searching a keyword like general ones and then finally purchased appropriate products by utilizing deal-prone keywords in the last time. Those two types of customers have the similar rates of purchase. However, the last type of the customer has middle deal-proneness; who utilizes deal-prone keywords in the middle of the process. This type of a customer closely gets into the information by employing deal-prone keywords but he/she could not find out appropriate alternative then would modify other keywords to look for other alternatives. That is the reason why the purchase probability in this case would be decreased Also, this research confirmed that there is a loyalty effect using location searching specificity. The customer who has higher trip loyalty for specificity location responds to selected promotion rather than general promotion. So, this customer has a lower probability to purchase.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.19-28
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• 2015

Korea Digital Copyright Exchange of Korea Copyright Commission runs and manages copyrighted works and copyright license agreement, as well as assigns Integrated Copyright Number(ICN) to copyrighted works, also offers copyrighted works searching service. Keyword-based searching method based on ICN metadata provides results depending on the inclusion of metadata keyword. However, keyword-based searching method has limitations that cannot provide exact results that users need. Therefore, the essential method of offering exact result is needed. In this paper, we propose the semantic-based searching method about copyrighted works to increase the accuracy of searching results by extending ICN matadata to ontology, and implement the ontology of copyrighted works by defining relation and semantics about metadata elements. In order to compare semantic-based searching based on the ontology of copyrighted works with keyword-based searching method, the search results of each method according to 5 scenarios are presented and the accuracy of each method is compared.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.880-886
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• 2016

With lots of information occurring on the Internet, the search engine plays a role in gathering the scattered information on the Internet. Some search engines show not only search result pages including search keyword but also search result numbers of the keyword. The number of keyword searching result provided by the Google search engine can be utilized to identify overall trends for this search word on the internet. This paper is aimed designing and realizing the system which can efficiently manage the number of searching result provided by Google search engine. This paper proposed system operates by Web, and consist of search agent, storage node, and search node, manage keyword and search result, numbers, and executing search. The proposed system make the results such as search keywords, the number of searching, NGD(Normalized Google Distance) that is the distance between two keywords in Google area.

• The Journal of Information Systems
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• v.8 no.2
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• pp.91-110
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• 1999

Recently, searching agent systems to help purchase of products between business and customer have been actively studied in Electronic Commerce(EC). However, the most of comparative searching agent systems are only provided customers with searching results by the keyword-based search, and is not support the efficient decision models to be selected products considering the customer's requirements. This paper proposes the decision agent system applied decision model as well as searching functions based on the keyword-input to be selected useful products in EC. The proposed decision agent system is consist of the user interface, provider interface, decision model. Especially, as the example of the decision model, this paper is designed and implemented the prototype of decision agent system which is normalized the searching data and value of customer's preference weight as to each attribute, and orderly provided customers with computed results. This agent system is also carried out sensitive analysis according to the reflection ratio of the each attribute.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1489-1515
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• 2022

The number of interconnected real-world devices such as sensors, actuators, and physical devices has increased with the advancement of technology. Due to this advancement, users face difficulties searching for the location of these devices, and the central issue is the findability of Things. In the WoT environment, keyword-based and geospatial searching approaches are used to locate these devices anywhere and on the web interface. A few static methods of indexing and ranking are discussed in the literature, but they are not suitable for finding devices dynamically. The authors have proposed a mechanism for dynamic and efficient searching of the devices in this paper. Indexing and ranking approaches can improve dynamic searching in different ways. The present paper has focused on indexing for improving dynamic searching and has indexed the Things Description in Solr. This paper presents the Things Description according to the model of W3C JSON-LD along with the open-access APIs. Search efficiency can be analyzed with query response timings, and the accuracy of response timings is critical for search results. Therefore, in this paper, the authors have evaluated their approach by analyzing the search query response timings and the accuracy of their search results. This study utilized different indexing approaches such as key-words-based, spatial, and hybrid. Results indicate that response time and accuracy are better with the hybrid approach than with keyword-based and spatial indexing approaches.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.39-55
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• 2013

It is a difficult problem to use keyword retrieval for low-quality Korean document images because these include adjacent characters that are connected. In addition, images that are created from various fonts are likely to be distorted during acquisition. In this paper, we propose and test a keyword retrieval system, using a support vector machine (SVM) for the retrieval of low-quality Korean document images. We propose a keyword retrieval method using an SVM to discriminate the similarity between two word images. We demonstrated that the proposed keyword retrieval method is more effective than the accumulated Optical Character Recognition (OCR)-based searching method. Moreover, using the SVM is better than Bayesian decision or artificial neural network for determining the similarity of two images.

• 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 the Korean Society for information Management
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• v.18 no.4
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• pp.183-200
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• 2001

The traditional way of access to image information is through descriptive keyword searching. However, many studies in image indexing and retrieval have reached a consensus on the difficulties and limitations of text-base image description. This research investigates the feasibility of using visual browsing that is being used comparatively much less than keyword searching. The effectiveness of Keyword access versus visual access were examined through experiments in which participants searched for pictures of specified emotions using different access modes: keywords only, visual browsing only, and the combination of both. It was found that keyword searching was appropriate for clean searches while visual browsing was the effective way to browse many pictures quickly, thus finding more relevant pictures. Findings and results can guide of images retrieval systems, especially the retrieval system of subjective and interpretive information.