• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.1
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• pp.97-119
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• 2017

This research investigated user satisfaction and importance of OPAC2.0 services in university libraries for book search result. This research analyzed OPAC2.0 services in university libraries focusing on book search result, user satisfaction with and importance in services, difference in satisfaction and importance, and grade and satisfaction. As a result of the investigation and analysis, OPAC2.0 services given the most was the service of 'portal site linkage'. Generally, the satisfaction with OPAC2.0 services was 2.07 in average, 'very dissatisfactory'. The service considered to be the most important was 'service item'. The difference between satisfaction and importance showed dissatisfactory result, compared with importance in general. The grade and the general difference in satisfaction didn't appear. On the basis of the analysis result mentioned above, with the purpose of the improvement in OPAC2.0 services focusing on book search result, it is necessary to manage users continuously by publicizing libraries concerning respective services, introducing use guide, offering a variety of services, improving quality, and offering information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.594-600
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• 2017

This paper proposes a global search based motion estimation algorithm for high performance HEVC encoder and its hardware architecture. To eliminate temporal redundancy, motion estimation in HEVC inter-view prediction uses global search and fast search algorithm to search for a predicted block having a high correlation with the current PU in an interpolated reference picture. The global search method predicts the motion of all candidate blocks in a given search area, thus ensuring optimal results, but has a disadvantage of large computation time. Therefore we propose a new algorithm that reduces computational complexity by reusing SAD operation in global search to reduce computation time of inter prediction. As a result of applying the proposed algorithm to standard software HM16.12, the computation time was reduced by 61%, BDBitrate by 11.81%, and BDPSNR by about 0.5% compared with the existing search algorithm. As a result of hardware design, the maximum operating frequency is 255 MHz and the total number of gates is 65.1K.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.727-731
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• 2010

Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.

• Journal of the Korean Home Economics Association
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• v.50 no.6
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• pp.99-117
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• 2012

This study aimed to measure consumer information competency, which indicates consumers' general ability to search and utilize information. The model of this study was constructed in order to identify how consumer information competency influences the efficiency and the effectiveness of external information search. The model was verified with related prior knowledge as a moderator variable in order to understand holistic consumer information search activity. The result of the study is as follows. First, the concept of consumer information competency was constructed with four sub-abilities: define, search, extract, and synthesis & use. The ability of define was the highest, as opposed to the ability of extract, which was the lowest. Second, consumer information competency was lower for women as well as for low family income. The sub-abilities of search and synthesis & use were lower for aging consumers. Third, consumer information competency has positive effects on information search efficiency and effectiveness. Moreover, the efficiency influences the effectiveness positively. Fourth, prior knowledge moderates the effect of consumer information competency to the efficiency. Only for consumers with high knowledge the efficiency has the effect of mediating between consumer information competency and the effectiveness.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.7-13
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• 2021

Purpose: Unemployment in its general form is a result stemming from the decisions of workers to search for a new and better paying job. In this study, the view that unemployed workers were not simply desiring any job, but one that would maximize their expected future outcome, was examined. Research design, data, and methodology: In order for collection of data and analysis, the panel dates of individual applications for job openings on job search websites were utilized to examine search effort and period for individuals. Results: It was found that the number of applications sent by a job seeker declined over their period of job searching, and that job seekers over a long duration of time tend to send relatively more applications per week throughout their entire search period. The latter finding contradicts the implications of the standard labor search effort models. Conclusions: It can be observed that these job search models fail to capture several key elements in search efforts, and that the search time for an offer is not entirely predetermined by the labor market conditions and socio-economic (individual) characteristics of the searcher. It can be shortened as he or she intensifies their job search efforts.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.227-233
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• 2016

Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.318-324
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• 2001

In this paper we propose the adaptive scheme to place more search points as long as the operation tapability of the motion estimator in the video codec permits. And the proposed algorithm takes advantage of the intuitive fact that the quality of the decoded video is more degraded as the spatial frequency of the corresponding block is increased due to the augmentation of local minima per unit area. Thererore, we propose the scheme to enhance the quality by locating relatively more search points in the block with high frequency components by analyzing the spatial frequencies of the video sequence. As a result, the proposed scheme can adaptively place more search points possibly permitted by the motion estimator and guarantees better quality compared to the TSS and FS.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.209-233
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• 2012

In this study in order to verify the overall information seeking behavior of the Web-based OPAC users, it was analyzed transaction log file for 7 years. Regarding Web-based OPAC information seeking behavior, it was studied from the perspective of information seeking strategy and information seeking failure. In search strategy, it was analyzed search type, search options, Boolean operator, length of search text, number of uses of word, number of use Web-based OPAC, number of use by time, by week day. Also, in search failure, search failure ratio, search failure ratio by search options, search failure ratio by Boolean operator were analyzed. The result of this study is expected to be utilized for OPAC system and service improvement in the future.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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• pp.436-453
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• 2022

This study aims to investigate the effects of fashion information search and innovativeness of consumers on service quality of image search. Furthermore, it focuses on exploring the effect of image search service quality on use intention. Data of mobile-friendly consumers in their 20s and 30s was collected in September 2021 via an online survey. Finally, 300 samples were used for the data analysis. First, motivation for information search in fashion was divided into four factors: information, relation, leisure, and entertainment motivation. Furthermore, service quality of image search was divided into four factors: accuracy, convenience, customization, and aesthetics. Second, regression analysis was conducted to evaluate the effect of fashion information search motivation on service quality. As a result, it was found that information, relation, and entertainment motivation except leisure motivation had significant effects on all factors of service quality. Third, fashion innovativeness had no significant effect on aesthetics while consumer innovativeness significantly influenced all factors of service quality. Fourth, accuracy, convenience, and aesthetics had a significant effect on use intention.