• Journal of Digital Contents Society
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• v.19 no.2
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• pp.301-307
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• 2018

Generally, search engine summarizes the main contents of the search results so that user can click the site providing the information of the contents to search first. In this study, we demonstrated whether the user clicks on the search results based on the summary content provided by the search engine or on the order of the search result placement through empirical studies through the presentation of search results. By using the API provided by the search engine company, a search site that presents the search results in a regular and inverse order is created, and the click action of each user's search result is displayed in the order of actual click order, click position, and the user's search type such as the route of movement. As a result of the analysis, most users account for more than 60% of users who click on the first and second exposed search results regardless of the search results. It is confirmed that the search priority of users is determined according to the order of search results regardless of the summary of search results.

• The Journal of Information Systems
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• v.25 no.1
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• pp.159-182
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• 2016

Purpose This paper aims to develop a novel tabu search algorithm for solving the sequencing problems with precedence constraints. Due to constraints, the traditional meta heuristic methods can generate infeasible solutions during search procedure, which must be carefully dealt with. On the contrary, the candidate order based tabu search (COTS) is based on a novel neighborhood structure that guarantees the feasibility of solutions, and can dealt with a wide range of sequencing problems in flexible manner. Design/methodology/approach Candidate order scheme is a strategy for constructing a feasible sequence by iteratively appending an item at a time, and it has been successfully applied to genetic algorithm. The primary benefit of the candidate order scheme is that it can effectively deal with the additional constraints of sequencing problems and always generates the feasible solutions. In this paper, the candidate order scheme is used to design the neighborhood structure, tabu list and diversification operation of tabu search. Findings The COTS has been applied to the single machine job sequencing problems, and we can see that COTS can find the good solutions whether additional constraints exist or not. Especially, the experiment results reveal that the COTS is a promising approach for solving the sequencing problems with precedence constraints. In addition, the operations of COTS are intuitive and easy to understand, and it is expected that this paper will provide useful insights into the sequencing problems to the practitioners.

• 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.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.163-170
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• 2002

Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces for realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. In order to accelerate the searching speed of T-search, a terrain database of triangular polygons is modeled in multi-levels by adopting the LOD (Level of Detail) method used in realtime computer graphics. Simulation results show that the new LOD search is effective in shortening the required computing time. The LOD search can be even further accelerated by introducing an NN (Neural Network) algorithm, in the cases where a appropriate range of moving paths can be predicted by cultual information of the simulated terrain, such as lakes, houses, etc.. Numerical tests show that LOD-NN search almost double the speed of the original T-search.

• Journal of Information Management
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• v.26 no.1
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• pp.80-98
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• 1995

Search strategies is a means to make an efficient search. Among several studies of search strategy, Bates' $\ulcorner$Search Tactics$\lrcorner$ has been often cited and introduced, but their studies have been superficial. In this paper, the contents of Bates' $\ulcorner$Search Tactics$\lrcorner$ are examined in detail, and we try to represent the actual online search process based upon Bates' $\ulcorner$Search Tactics$\lrcorner$. The following three kinds of survey are made in order to clarify which and how tactics are used: (1) Interview with 7 searchers who belong to different types of organizations, and use different kinds of databases (2) Analysis of some online search records. (3) Analysis of written applications for a newspaper database during one year. In conclusion, Bates' tactics falls into categories and new several tactics which often used are added. The following five factors affect online search activities, search strategy, and search tactics. (1) the difficulty of search requests (2) the kinds of databases (3) the charging policy for each online search (4) the presence of the user during the search (5) the searcher' online experience In the limited condition, typical tactics are suggested, but in order to generalize the pattern of using tactics, further investigation is necessary.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.1-14
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• 2016

Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.9-12
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• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.681-687
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• 2003

Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces fur realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and the T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in a successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. The dynamic T-search, which is proposed in this paper, combines conventional T-search and the concept of the dynmaic-window search which uses reduced searching windows or sets of triangular surface polygons at each frame by taking advantage of the information regarding dynamic charactereistics of a simulated vehicle. Numerical tests show improvement of searching speeds by about 5% for randomly distributed triangles. For continuous search following a vehicle path, which occurs in actual vehicle simulation, the searching speed becomes 4 times faster.

• Journal of Korean Library and Information Science Society
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• v.22
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• pp.139-169
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• 1995

The purpose of this study is to analyze the search pattern and search outcome of the National Central Library OPAC users by measuring their success rates and identifying the factors of failure and the personal background which bring about the differences of the search outcome. Various methods have been used for the study. Personal interview was used to find the pattern of the search, observation method was used to investigate the search process and the failure factors, and a questionnaire was used to survey personal background of searchers. The data were collected during the period of 7 days from April 17, 1995 through April 23, 1995. The search of 1, 217 cases, sampling systematically 25% out of the whole users, were collected and analyzed for the study. The findings of the study can be summarized as follows : First, in regard to the pattern, known-item search(72.6%) was preferred to the subject search(27.4%) and in case of known-item search the access point used were in the order of title, author, title and author. Second, the overall success rate of known-item search was 50.3% and the success rates were in order of author and date, title, and author. The failure factors of known-item search were divided into users factor of 67% and the database factor of 33%, respectively. Third, in case of subject search, its overall success rate was 44.1% and the keyword was the major access point, and the average of precision ratio was very low. Fourth, the analysis of the personal background related to the search outcome has shown significant differences by sex, the experience of using OPAC, education level, and the frequency of using other information retrieval systems. Based on the results the following suggestions can be made to improve the search outcome : First, the system should be su n.0, pplemented online help function to assist users to overcome the failure during search. Second, user instruction in group or individual should be implemented for the users to understand the system.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.41-48
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• 2008

This study focuses on the modeling file search engine and suggesting modified file search schema based on weight value using file contents in order to improve the performance in terms of search accuracy and matching time. Most of the file search engines have used string matching algorithms like KMP(Knuth.Morris.Pratt), which may limit portability and fast searching time. However, this kind of algorithms don't find exactly the files what you want. Hence, the file search engine based on weight value using file contents is proposed here in order to optimize the performance for mobile environments. The Comparison with previous research shows that the proposed schema provides better.