• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.111-129
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• 2009

This study examined the usability of text-based search and visual search of a large multidisciplinary library database to provide an empirical analysis of the acceptability of visual systems in the information retrieval environment. It also examined if there are differences in the usability assessment based on experimental order. The results indicated that the text-based search supported users' search behaviors more efficiently than the visual search. Also the text-based search was rated higher than the visual search in terms of user perceptions of four usability factors.

• Journal of Korean Library and Information Science Society
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• v.39 no.1
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• pp.265-278
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• 2008

This study aims to perform an evaluation of unified search services provided by major Korean search portals, Naver, Daum, Yahoo-Korea, and Empas. These unified search services are evaluated in terms of the relevance of search results. In conducting this study, real queries that real users submitted were used. This study also utilized click logs that consist of documents users clicked and viewed. The results of this study can be implemented to the development and improvement of portal's unified search services. Users can refer to the results of this study in choosing unified search services from search portals.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.3
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• pp.289-334
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• 2018

Even though information in many languages other than English is quickly increasing, English is still playing the role of the lingua franca and being accounted for the largest proportion on the web. Therefore, it is necessary to investigate the key features and differences between "information searching behavior using mother tongue as a search language" and "information searching behavior using English as a search language" of users who are non-mother tongue speakers of English to acquire more diverse and abundant information. This study conducted the experiment on the web searching which is applied in concurrent think-aloud method to examine the information searching behavior and the cognitive process in Korean search and English search through the twenty-four undergraduate students at a private university in South Korea. Based on the qualitative data, this study applied the frequency analysis to web search pattern under search language. As a result, it is active, aggressive and independent information searching behavior in Korean search, while information searching behavior in English search is passive, submissive and dependent. In Korean search, the main features are the query formulation by extract and combine the terms from various sources such as users, tasks and system, the search range adjustment in diverse level, the smooth filtering of the item selection in search engine results pages, the exploration and comparison of many items and the browsing of the overall contents of web pages. Whereas, in English search, the main features are the query formulation by the terms principally extracted from task, the search range adjustment in limitative level, the item selection by rely on the relevance between the items such as categories or links, the repetitive exploring on same item, the browsing of partial contents of web pages and the frequent use of language support tools like dictionaries or translators.

• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.265-289
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• 1994

Databases publicly available for online searching permit both citation and subject searching, however, subject searching has dominated the online search environment. Despite the power of citation searching, it may be underutilized This study explored the relationship between the number of cited references used in a citation search and information retrieval effectiveness, a relatively unstudied phenomenon. Three articles in the library and information science literature were chosen to represent sample questions. Cited reference searches were conducted for each article and each of its references. All searches were conducted in Social Scisearch and Scisearch on DIALOG. Relevance judgments on the retrieved citations were obtained from the authors of the original articles. This research focused on analyzing, in terms of information retrieval effectiveness, the overlap among postings sets retrieved by various combinations of cited references. The findings from the three case studies clearly showed that the more cited references used for the citation search, the better the performance, in terms of retrieving more relevant documents, up to a point of diminishing retums. In addition, generally the overall level of overlap among relevant documents sets was found to be low. Therefore, if only some of the cited references among many candidates are used for a citation search, a significant proportion of relevant documents may be missed. The analysis of the characteristics of cited references provided the ways to predict which cited refereces would be useful to improve information retrieval. The findings of this comprehensive exploratory study are of interest for both theoretical and practical reasons. They contribute to the development of a theoretical model for the effective use of the citation search. This model might also be implemented in operational online systems. In addition, the findings potentially will help online searchers improve their search strategies using the citation search so that they can better achieve their information retrieval goals: the retrieval of items relevant to a given question and the suppression of nonrelevant items.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1097-1100
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• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.290-294
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• 2021

Experts have designed popular and successful model architectures, which, however, were not the optimal option for different scenarios. Despite the remarkable performances achieved by deep neural networks, manually designed networks for classification tasks are the backbone of object detection. One major challenge is the ImageNet pre-training of the search space representation; moreover, the searched network incurs huge computational cost. Therefore, to overcome the obstacle of the pre-training process, we introduce a network adaptation technique using a pre-trained backbone model tested on ImageNet. The adaptation method can efficiently adapt the manually designed network on ImageNet to the new object-detection task. Neural architecture search (NAS) is adopted to adapt the architecture of the network. The adaptation is conducted on the MobileNetV2 network. The proposed NAS is tested using SSDLite detector. The results demonstrate increased performance compared to existing network architecture in terms of search cost, total number of adder arithmetics (Madds), and mean Average Precision(mAP). The total computational cost of the proposed NAS is much less than that of the State Of The Art (SOTA) NAS method.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.317-342
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• 2024

The purpose of this study is to explore ways to improve accessibility to school library materials through analysis of elementary school students' information search behavior in DLS. Accordingly, the DLS search process was recorded for 26 students attempting a DLS search in the school library, and data was collected through a pre-search questionnaire on overall information needs and a post-search questionnaire on the search process and results. As a result of the analysis, satisfaction was found to be low when the main purpose of DLS use was simple leisure reading, when the search time and number of search words were long, and when there were too many search results. Accordingly, it was emphasized that curriculum subject-related metadata elements should be developed and a curriculum subject-specific thesaurus should be built and used to build lists and support user searches. In addition, it was suggested that the basic functions provided in external searches should be included, and a foundation should be laid in terms of resources and curriculum to systematically provide information utilization education to elementary school students who lack the ability to select search terms and judge the suitability of results after the search. It was proposed to provide an integrated search service with external resources and a personalized book recommendation service.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.533-543
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• 2012

We in this paper propose a semantic search system based on Korean medicine ontology. Semantic search augments search results and improves search accuracy by understanding which concept denotes terms which users is trying to find. Our semantic search system also provides these semantic search capabilities. Moreover, search scenarios which is meaningful in Korean medicine are designed and implemented by analyzing the semantics of Korean medicine ontology. Therefore, our system can help users find the useful search results with respect to Korean medicine by providing the more meaningful information as well as the connected information in ontology.

• Journal of the Korean Society for information Management
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• v.16 no.2
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• pp.49-80
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• 1999

This study analyses the researches on automatic query modification, expansion and combination based on search results of natural language queries and gives a conceptual framework for the factors affecting the effectiveness of the relevance feedback. The operating and experimental systems based on the vector space model, the binary independence model and the inference net model are reviewed, and it is found that the effectiveness of query expansion is affected by conceptual models, algorithms for weighting terms and documents and selecting query terms to be added, size of relevant and non-relevant documents to be used and size of terms to be added in relevance feedback, query length, type and size of DBs, etc.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.188-191
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• 2002

To reduce the bit-rate of video sequences by removing temporal redundancy, motion estimation techniques have been developed. However, the high computational complexity of the problem makes such techniques very difficult to be applied to high-resolution applications in a real time environment. For this reason, low computational complexity motion estimation algorithms are viable solutions. If a priori knowledge about the motion of the current block is available before the motion estimation, a better starting point for the search of n optimal motion vector on be selected and also the computational complexity will be reduced. In this paper, we present an adaptive block matching algorithm based on temporal correlations of consecutive image frames that defines the search pattern and the location of initial starting point adaptively to reduce computational complexity. Experiments show that, comparing with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(㏈) better than DS in terms of PSNR and improves as much as 50% in terms of the average number of search points per motion estimation.