• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.279-306
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• 2023

This study analyzed bibliographic attributes related to the selection and use of reading materials based on data on books borrowed or purchased together in order to understand the properties of reading materials that have complex user needs from various perspectives. As a result of creating co-occurrence matrices of bibliographic attribute terms by dividing them into 26 sub-attribute units related to KDC main class, target reader, and user age, and performing network analyses, the details and prominent mediating role of bibliographic attributes of reading materials were identified. The results of this study will be helpful in designing facets of reading information systems, including library OPAC, in the future.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.201-208
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• 2015

With services such as SNS and facebook, Big Data popularize the use of small size such as micro blogs are increasing. However, the problem of accuracy and computational cost of the search result of big data of a small size is unresolved. In this paper, we propose a subnet selection techniques based probability to improve the browsing speed of the small size of the text information from big data environments, such as micro-blogs. The proposed method is to configure the subnets to give to the attribute information of the data increased the probability data search speed. In addition, the proposed method improves the accessibility of the data by processing a pair of the connection information between the probability of the data constituting the subnet to easily access the distributed data. Experimental results showed the proposed method is 6.8% higher detection rates than CELF algorithm, the average processing time was reduced by 8.2%.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• The Korean Journal of Food And Nutrition
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• v.35 no.6
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• pp.481-490
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• 2022

The influence of the food value consumption type of MZ generation on food choice attribute and sustainable food consumption behavior was studied using structural equation modeling. A survey was conducted on April 11~17, 2022, among panels aged 20 to 39. A total of 350 valid replicates (100%) were analyzed using statistical program SPSS The validity of the measurement instrument was verified through exploratory factor analysis and confirmatory factor analysis. The data reliability was confirmed using Cronbach's alpha coefficient. The hypothesis was verified by performing path analysis through structural equation modeling using AMOS. Regarding the influence of food choice characteristics on sustainable food consumption behavior, health has a significant positive (+) effect on the selection consumption behavior of certified food and local food. Among food value consumption categories social value consumption has a significant negative (-) influence on the consumption behavior of certified food and the choice of local food. Ethical value consumption has a significant positive (+) influence on the selection consumption behavior of certified food and local food. This study is significant because it has identified sustainable food consumption behaviors that domestic consumers can adopt daily. It can use as baseline data for preparing political and institutional measures.

• Culinary science and hospitality research
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• v.24 no.3
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• pp.25-34
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• 2018

The purposes of this study were to examine the effect of Home Meal Replacement (HMR) selection attributes on attitude and repurchase intention and to investigate the moderating role of brand trust between attitude and repurchase intention. This study surveyed the customers who have purchased HMR in Seoul and Gyeonggi area using a convenience sampling method. The survey was conducted from September 15, 2017 to October 25, 2017. A total of 250 questionnaires were distributed, and 237 copies were collected. Of these, 228 copies were used as valid data. The results of the analysis were as follows. First, convenience of the HMR selection attribute had a significant effect on attitude, and food quality and packaging had no significant effect on attitude. Second, attitude toward HMR had a significant effect on repurchase intention. Third, brand trust played a moderating role between HMR attitude and repurchase intention. Therefore, it is necessary for HTMcompanies to understand consumers' attitudes and consumption behaviors accurately by recognizing the selection attributes that consumers consider important By gaining strong brand trust, companies could increase repurchase intention.

• Korean journal of food and cookery science
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• v.27 no.2
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• pp.83-94
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• 2011

The purpose of this study was to analyze the structural relationships among selection attributes, satisfaction, and loyalty of green tea consumers, including their moderating effect of involvement. Questionnaires were administered to residents of Seoul and Gyeonggi-do province, who were 20 years old and older and who had purchased green tea. A total of 700 questionnaires were distributed, and 658 were finally used in the analysis. SPSS 15.0 and LISREL 8.80 were used for the analysis. Selection attributes had a significant effect on satisfaction, and statistical significance was observed with regard to factors such as marketing, production, sensory evaluation, and brand. No significant direct effect was observed between selection attributes and loyalty. Additionally, satisfaction had a significant effect on loyalty. The marketing factor had a negative effect on satisfaction in both the low- and high-involvement groups. The brand factor had a positive effect on satisfaction in the low involvement group, suggesting that developing and promoting a popular brand is essential. Sensory and utility factors had a positive effect on satisfaction in the high involvement group.

• The Journal of Economics, Marketing and Management
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• v.11 no.1
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• pp.13-19
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• 2023

Purpose: This study aims to determine which optional attributes are more important for the MZ generation when purchasing luxury fashion goods. Although sales are slowing down in all industries due to COVID-9, sales of luxury fashion goods are instead increasing, centered on the MZ generation. Companies are expanding online sales channels and transforming to gain more attention. Research design, data and methodology: Selection attributes are considered to be more crucial, when customers select luxury fashion products such as prestige image, brand awareness, reasonable price, and product quality, were researched and also find the correlation between satisfaction and purchase intention were analyzed. A survey was conducted focusing on the MZ generation, and the contents of the survey were analyzed using the SPSS 22.0 program and the Amos 26.0 program. Results: As a result of the study, selection attributes as prestige image, brand awareness, and product quality were proved to influence significantly on satisfaction. Moreover, the path of satisfaction to purchase intention proved significant. But reasonable price did not influence on MZ generations satisfaction. Conclusions: The research results present the selection attributes of luxury fashion products and provide significant implications when the MZ generation selects the attributes of luxury fashion products.

• Journal of the military operations research society of Korea
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• v.30 no.1
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• pp.1-14
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• 2004

In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.

• Korean Journal of Human Ecology
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• v.9 no.1
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• pp.63-70
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• 2000

The purpose of this study is The results was that consumers who like to the top brand's commodities, had commonly high tendency to and fro its trademark and store allegiance. Furthermore, they have usually bought something following on their inclination what they had purchased as well as the store decoration character and the marketing promotion attribute. The other consumers who prefer to the discount store's merchandises, had also high propensity and the biggest influence on buying something which were those factors; their instance shopping habit, utility-economy trait, follow the fashion character and strong circumspection tendency besides using the mass media Info., personal data and commodities' attribute.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.1-12
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• 2016

In this paper, we propose an approach that efficiently builds regional hazardous weather prediction models based on past weather data. Doing so requires finding the proper weather attributes that strongly affect hazardous weather for each region, and that requires a large number of experiments to build and test models with different attribute combinations for each kind of hazardous weather in each region. Using our proposed method, we reduce the number of experiments needed to find the correct weather attributes. Compared to the traditional method, our method decreases the number of experiments by about 45%, and the average prediction accuracy for all hazardous weather conditions and regions is 79.61%, which can help forecasters predict hazardous weather. The Korea Meteorological Administration currently uses the prediction models given in this paper.