• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.356-364
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• 2000

Block based fast motion estimation algorithm use the fixed search pattern to reduce the search point, and are based on the assumption that the error in the mean absolute error space monotonically decreases to the global minimum. Therefore, in case of many local minima in a search region we are likely to find local minima instead of the global minimum and highly rely on the initial search points. This situation is evident in the motion boundary. In this paper we define the candidate regions within the search region using the motion information of the neighbor blocks and we propose the multiple local search method (MLSM) which search for the solution throughout the candidate regions to reduce the possibilities of isolation to the local minima. In the MLSM we mark the candidate region in the search point map and we avoid to search the candidate regions already visited to reduce the calculation. In the simulation results the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary. Especially, in PSNR the proposed method obtains similar estimate accuracy with the significant reduction of search points to that of full search.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.625-629
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• 2001

A cyber shopping mall is a place where consumers acquire product information, and make purchase decisions in the cyber space. Even though it offers many advantages over traditional malls, there are still several limitations to do shopping in an existing cyber mall. One of these limitations is the absence of an efficient shopping aid to compare multiple items from multiple malls. Existing search systems usually support a keyword search with limited conditions. Consumers spend lots of their time to compare multiple alternatives from search results. In this paper, we propose an intelligent product search system. There are two main features in our system. The first one is a full support of comparison shopping with multiple perspectives based on commercial search engines. The second one is an enhancement to the shopping aid based on a new concept of Shopping AssistanT. Our system is implemented in Visual Basic and PERL, and experimental results show a satisfactory performance.

• The Journal of Information Systems
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• v.29 no.1
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• pp.289-301
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• 2020

Purpose This study analyzes whether Internet search of cryptocurrency has a causal relationship to return and volatility of cryptocurrency. Design/methodology/approach Google Trend was used as a measure of the level of Internet search, and the parametric tests of Granger causality in the 1st moment and the 2nd moment were adopted as the analysis method. We used Bitcoin's dollar-based price, which is the No. 1 market value among cryptocurrency. Findings The results showed that the Internet search measured by Google Trends has a causal relationship to cryptocurrency in both average and volatility, while there is a difference in causality and its degree according to the search area and category that Google Trend user should set. Because the Granger causality is based on the improvement of prediction, the analysis results of this study indicate that Internet search can be used as a leading indicator in predicting return and volatility of cryptocurrency.

• Journal of the Korean Society for information Management
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• v.17 no.2
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• pp.85-100
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• 2000

Meta search engines have been used as the first engine because they let users several search engines at once for their queries and give them the search results. The purpose of this study is to examine the features and functions of 17 meta search engines in order that it helps users select and execute effective searches on meta search engines. Each selected engine is analyzed based on the criteria evaluating both meta search engines and general search engines. The results show that each meta search engine has its own characteristics while there are common features among them. It is expected that the results of this study will help users utilize meta search engines and provide meta search engine designer basic ideas.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.18-30
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• 2020

Recently, as graph-structured data is widely used in various fields such as social networks and semantic Webs, needs for an effective and efficient search on a large amount of graph data have been increasing. Previous keyword-based search methods often find results by considering only the relevance to a given query. However, they are likely to produce semantically similar results by selecting answers which have high query relevance but share the same content nodes. To improve the diversity of search results, we propose a top-k search method that finds a set of subtrees which are not only relevant but also diverse in terms of the content nodes by controlling their similarity. We define a criterion for a set of diverse answer trees and design two kinds of diversified top-k search algorithms which are based on incremental enumeration and A^⁎ heuristic search, respectively. We also suggest an improvement on the A^⁎ search algorithm to enhance its performance. We show by experiments using real data sets that the proposed heuristic search method can find relevant answers with diverse content nodes efficiently.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.239-254
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• 2006

An efficient descent method for unconstrained optimization problems is line search method in which the step size is required to choose at each iteration after a descent direction is determined. There are many ways to choose the step sizes, such as the exact line search, Armijo line search, Goldstein line search, and Wolfe line search, etc. In this paper we propose a new inexact line search for a general descent method and establish some global convergence properties. This new line search has many advantages comparing with other similar inexact line searches. Moreover, we analyze the global convergence and local convergence rate of some special descent methods with the new line search. Preliminary numerical results show that the new line search is available and efficient in practical computation.

• ETRI Journal
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• v.34 no.3
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• pp.369-378
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• 2012

In this paper, we propose new adaptive search range motion estimation methods where the search ranges are constrained by the probabilities of motion vector differences and a search point sampling technique is applied to the constrained search ranges. Our new methods are based on our previous work, in which the search ranges were analytically determined by the probabilities. Since the proposed adaptive search range motion estimation methods effectively restrict the search ranges instead of search point sampling patterns, they provide a very flexible and hardware-friendly approach in motion estimation. The proposed methods were evaluated and tested with JM16.2 of the H.264/AVC video coding standard. Experiment results exhibit that with negligible degradation in PSNR, the proposed methods considerably reduce the computational complexity in comparison with the conventional methods. In particular, the combined method provides performance similar to that of the hybrid unsymmetrical-cross multi-hexagon-grid search method and outstanding merits in hardware implementation.

• Journal of Fashion Business
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• v.22 no.4
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• pp.160-177
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• 2018

The objective of this study was to investigate mediation effect of appearance management behavior on the relationship between satisfaction of personal image and job search efficacy. Based on previous studies on components of personal image, appearance management behaviors, and job search efficacy, questionnaire items were developed. For this study, we conducted a questionnaire survey among 422 students from women's university in Seoul. Statistical analyses were performed using SPSS 23. Results are as follows. First, there were positive and moderate bivariate correlations among satisfaction of personal image, appearance management behavior, and job search efficacy. Second, satisfaction of personal image was found to have a partially significant effect on job search efficacy while satisfaction of internal image, visual image, and social image had a positive effect on job search skill. Satisfaction of internal image had a positive effect on job search strength. However, satisfaction of visual image or social image did not have a significant effect on job search strength. Third, fashion management behavior among components appearance management behavior could partially mediate the relationship between satisfaction of personal image and job search efficacy, indicating that satisfaction of internal image and visual image among components personal image not only has a direct effect on job search skill among job search efficacy, but also has an indirect effect on job search skill by affecting fashion management behavior. These results suggest that it is important to build personal image effectively and increase satisfaction with oneself through active appearance management behavior to improve job search efficacy.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.395-412
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• 2010

This study aims to perform an evaluation of multimedia search services provided by major Korean search portals: Naver, Nate, Daum, Yahoo-Korea, Paran, and Google-Korea. These multimedia search services are evaluated in terms of the metadata of search results, search functionalities, searching methods, other functionalities, and display options. Every search portal offers image and video searching, whereas only Naver, Nate, and Daum offer music searching. Advanced searching methods and functions are mostly developed and supported in image and video searching rath than music searching. Naver, Nate, and Daum support various searching functions which search portals abroad have not developed. Google-Korea supports advanced searching functions. Search portals provide a limited number of metadata in search results. This study could contribute to the development and improvement of portal's multimedia search services.

• Journal of Fashion Business
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• v.21 no.5
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• pp.78-90
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• 2017

This study investigates the effects of appearance management behaviors on job search efficacy among female college students. Based on previous studies on appearance management behaviors and job search efficacy, the questionnaire items were developed. For the study, we conducted a questionnaire survey among 312 students from women's university in Seoul. The statistical analyses were performed using SPSS 23. The results were as follows. First, three types of appearance management factors have been identified: 'fashion & hair,' 'skin care & plastic surgery,' and 'body shape'; the reliability and validity of these factors were proved. Second, the appearance management behavior of female college students found to have a partially significant effect on job search efficacy: fashion & hair factor had a positive effect on job search strength; fashion & hair factor and body shape factor had a positive effect on job search skills. While skin care & plastic surgery factor had a negative effect on job search strength and job search skill. Third, between academic years, there were differences in job search efficacy but not in appearance management behavior. By majors, there were differences among skin care & plastic surgery factor, body shape factor, and job search strength factor. These results suggest that to improve the job search efficacy, proper appearance management through fashion and hair, and body shape management is necessary. In addition, it suggests that it is important to improve the effectiveness of employment by establishing the appearance management strategy that matches the characteristics of each major.