• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.165-171
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• 2003

Visual search in an unstructured search field is a fruitful research area for computational modeling. Search models that describe relationship between search time and probability of target detection have been used for prediction of human search performance and provision of ideal goals for search training. Until recently, however, most of models were focused on detecting a single target in a search field, although, in practice, a search field includes multiple targets and search models for multiple targets may differ from search models for a single target. This study proposed a random search model for multiple targets, generalizing a random search model for a single target which is the most typical search model. To test this model, human search data were collected and compared with the model. This model well predicted human performance in visual search for multiple targets. This paper also proposed how to determine optimal stopping time in multiple-target search.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.479-484
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• 2004

It is the present situation that the relevant data with the compensation and payment is filed and managed in the form of document or Excell. In case of the large volume dam construction, the management of the data about the sinking areas is conducted inefficiently in view of time management and economy through using the administrative manpower and data formating manpower. There is also problem about where and how to keep the data owing to the enormous data. As a result of the raised questions, through constructing the system which is linked with the location information and property information which is relevant to the compensation to increase the applying value of the information about the compensation and apply document management system to the geographic information system, the management system through computerizing for searching the uncompensated areas in appropriate areas and compensation information in the compensated areas is projected. Through constructing geographic information system, it is expected to create various information effects, using the function of the necessary area search for the boundary survey, actual condition survey, uncompensated area search, and re-compensated area search.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.3
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• pp.32-40
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• 1999

In this paper, we present a fast block matching motion estimation algorithm based on successive elimination algorithm (SEA). Based on the characteristic of center-biased motion vector distribution in the search area, the proposed method improves the performance of the SEA with a reduced the number of the search positions in the search area, In addition, to reduce the computational load, this method is combined with both the reduced bits mean absolute difference (RBMAD) matching criterion which can be reduced the computation complexity of pixel comparison in the block matching and pixel decimation technique which reduce the number of pixels used in block matching. Simulation results show that the proposed method provides better performance than existing fast algorithms and similar to full-search block motion estimation algorithm.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.43-45
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• 2000

For motion estimation, the block matching algorithm is widely used to improve the compression ratio of low bit-rate motion video. As a newly developed fast search algorithm, the nearest-neighbors search technique has a drawback of degrading video quality while providing fisher speed in search process. In this paper, a modified nearest-neighbors search algorithm is proposed in which a double rectangular shaped search-candidate area is used to improve video quality in encoding process with a small increasing of search time. To evaluate the proposed algorithm. other methods based on the nearest-neighbors search algorithm are investigated.

• Journal of the Korean Institute of Oriental Medical Informatics
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• v.15 no.1
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• pp.1-10
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• 2009

In these days everyone search the information easily with the Internet as the rapid distribution and active usage of the Internet. The search engines were developed specially to accuracy of information retrieval. User search the information more quickly and variously with them. The search portal system will be embossed with representation and basic services. The Internet user needs the result of text, image and video, knowledge search. The keyword based search is used generally for getting result of the information retrieval and another method is category based search. This paper investigates the classification of knowledge search structure for oriental medicine in market leader of search portal system by ranking web site. As a result, each classification system is unified and there is a possibility of getting up a many confusion to the user who approaches with classification systematic search method. This treatise proposed the improved oriental medicine classification system of internet information retrieval in knowledge search area. if the service provider amends about the classification system, there will be able to guarantee the compatibility of data. Also the proper access path of the knowledge which seeks is secured to user.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.93-112
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• 2009

Recently in the area of the information environment, there are lively discussions about search 2.0 which is representative of the next generation search services. In this study, we divide information search model into matching and linking models according the developmental stages. Therefore, on the one hand, we analyze the background, main concepts, related attributes and cases of the next generation search services and the other, we identify the representative keywords by the group analysis of various attributes and cases of it. The result shows that the main keywords such as social search, artificial intelligence and semantic search, and relation/network based search are representative of the search 2.0.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.9_10
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• pp.1396-1407
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• 2007

The purpose of this study was to identify the effect of clothing involvement, store and brand loyalty orientation on the information search behavior. The study subjects comprised 298 females living in Seoul and Kyung-gi area. The data were analyzed with factor analysis, regression, cluster analysis, ANOVA and correlation analysis. Clothing involvement and information search behavior consisted of various factors. Clothing involvement, store and brand loyalty influenced information search behavior. Fashion and clothing involvement was the most important factor which influenced all loyalty and information search behavior(i.e. brand and store loyalty, personal and nonpersonal information search behavior). According to store and brand loyalty factors, female consumers classified into three groups : low loyalty, brand loyalty and store loyalty group. Three groups showed different clothing involvement, information search, clothing purchasing behavior and demographic variables. Therefore, loyalty orientation is the important factor which can describe the consumer behavior more effectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.57-59
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• 2006

The purpose of search problem is to maximize the probability of target detection as limited search capability. Especially, as elapsing of time at a point of time of initial information received the target detection rate for searching an expected location due to a moving target such that wrecked ship or submarine decrease in these problems. The algorithm of search problem to a moving target having similar property of above targets should solve the search route as quickly as possible. In existing studies, they have a limit of applying in practice due to increasing computation time required by problem size (i.e., number of search area, search time). In this study, we provide that it takes more reasonable computation time than preceding studies even though extending a problem size practically using an approximate computation of probability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.772-774
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• 2017

Currently, there are many simple searches for local culture and tourism, but systematic information retrieval using ontology technology is weak. The keyword-based search, which is an existing search method, derives a search result that is different from a user's wanted intention. On the other hand, semantic search using ontology constructs shows the information related to the search term by creating a relation between words and words. Therefore, when tourists search for cultural and tourist attractions in the area, they provide information that includes meaning relevance in the search results. If the ontology provides information on the culture, sightseeing area, transportation, Can be more easily grasped. In this paper, we propose an ontology-based retrieval system based on culture and tourist sites utilizing public institutions database by using mobile application by extending search system which relied only on existing internal database to provide accurate and reliable information to users. This efficient structure of the ontology makes it possible to provide information suitable for the user quickly and accurately.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.93-102
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• 1996

For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.