• Korean Journal of Child Studies
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• v.37 no.6
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• pp.119-132
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• 2016

Objective: The purpose of this study was to analyze the operation and personal information management of public and private kindergarten homepages. Methods: A total of 2,846 kindergartens were selected from the I-Sarang portal service for analyzing operation, and 217 self-operating homepages were selected for evaluating management. Seven evaluation items from three domains (information gathering procedures and scope, information security, and management of file exposure protection) were used. Wireshark and Google were used for analyzing some evaluation items. Results: The operating ratio of kindergarten homepages was low and most of the kindergartens self-operated their homepages. The evaluation of the information gathering procedures and scope showed that the rule of consent process was not rigidly followed but that the rule of legality for information gathering was followed. Items related to information security were followed at very low levels. As for the management of file exposure protection, the evaluation of items related to the prevention of attachment disclosure showed that the rule of protecting personal information included in an attached file was followed but that the notice regarding information protection was not. Across all evaluation items, the level of personal information management was higher in public (vs. private) kindergartens. Conclusion: These results indicate methods to more securely and effectively manage personal information on kindergarten homepages.

• Asia pacific journal of information systems
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• v.14 no.4
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• pp.87-97
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• 2004

One of the most fundamental problems in business is ranking items with respect to profit based on historical transactions. The difficulty is that the profit of one item comes from its influence on the sales of other items as well as its own sales, and that there is no well-developed algorithm for estimating overall profit of selected items. In this paper, we developed a product network based on association rule and an algorithm for profit estimation and item selection using the estimated profit ranking(EPR). As a result of computer simulation, the suggested algorithm outperforms the individual approach and the hub-authority profit ranking algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.1
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• pp.1-8
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• 2002

The traditional approaches of association rule mining have relied on high support condition to find interesting rules. However, in some application such as analyzing the web page link and discovering some unusual combinations of some factors that have always caused some disease, we are interested in rules with high confidence that have very low support or need not have high support. In these cases, the traditional algorithms are not suitable since it relies on first satisfying high support. In this paper, we propose a new model, CP(Confidence Pattern)-Tree, to identify high confidence rule between 2-items without support constraint. constraint. In addition, we discuss confidence association rule between two more items without support constraint.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.403-412
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• 2013

This study figures out the concepts of container transport, logistical cost and the distribution of a company through studying documents, and to suggest logistical cost reduction approach, focused on the efficiency of transport which occupied the considerable portion of the total logistical cost of the company. We analyze and discuss the container loading of multiple items for multiple places of departure and arrival through a case study on S company in South Korea. We suggest a direction to reduce the logistical cost of the companies, analyzing the conditions of multiple items loading, and rule-based systems including an algorithm which determines container-loading for minimum freight expenses. We use data mining and OLAP tools of MS Analysis Services to produce loading rules for multiple items loading and generate OLAP cube and decision trees to validate the rules.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.25-38
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• 2004

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. In this paper we present the relation between the measure of association based on chi square statistic and the criteria of association rule for nominal database and propose the objective criteria for association.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.717-725
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• 2012

Data mining is a method to find useful information for large amounts of data in database. One of the well-studied problems in data mining is exploration for association rules. Association rule mining searches for interesting relationships among items in a given database by support, confidence, and lift. If we use the existing association rules, we can commit some errors by information loss not to consider the size of occurrence frequency. In this paper, we proposed a new association rule thresholds considering the number of possible rules of interest items and compare with existing association rule thresholds by example and real data. As the results, the new association rule thresholds were more useful than existing thresholds.

• Advances in Computational Design
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• v.8 no.2
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• pp.179-190
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• 2023

In this paper, building information modelling (BIM) associated to the principle of significant items emerged at quantities and costs in the optimization of productivity related to the rehabilitation of the building where proposed and discussed. A quantitative and qualitative study related to the field of application based on some parameters such as pathology diagnosis, projects documents and bills of quantities were used for model development at the preliminary stage of this work. The study identified 14 quantities significant items specified to cost value based on the use of the 80/20 Pareto rule, through the integration of building information modelling (BIM) in the optimisation of labour productivity for rehabilitation of buildings. The results of this study reveal the reliability and the improvement of labour productivity using building information modelling process integrating quantities and cost significant items.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.210-214
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• 2002

Association rule mining is an exploratory learning task to discover some hidden dependency relationships among items in transaction data. Quantitative association rules denote association rules with both categorical and quantitative attributes. There have been several works on quantitative association rule mining such as the application of fuzzy techniques to quantitative association rule mining, the generalized association rule mining for quantitative association rules, and importance weight incorporation into association rule mining fer taking into account the users interest. This paper introduces a new method for generalized fuzzy quantitative association rule mining with importance weights. The method uses fuzzy concept hierarchies fer categorical attributes and generalization hierarchies of fuzzy linguistic terms fur quantitative attributes. It enables the users to flexibly perform the association rule mining by controlling the generalization levels for attributes and the importance weights f3r attributes.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.195-209
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• 2003

Making traditional plan of target marketing based on association rule has brought restriction to obtain the target of marketing. This paper is to present inverse association rule as a new association rule for target marketing. Inverse association rule does not use information about relation between items that customers purchase, but use information about relation between items that customers do not purchase. By adding inverse association rule to target marketing, we generate new marketing strategy to look for new target of marketing. There are three steps to apply the marketing strategy proposed by this Paper to target marketing. Firstly, a database is converted to an inverse database. Although inverse association rules can be generated from a database, it is easier to explain inverse association rule in an inverse database than in a database. Secondly, association rules and inverse association rules are generated from inverse database. Finally, two types of rules which are created in the previous steps are applied to target marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.

• Agribusiness and Information Management
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• v.4 no.2
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• pp.14-21
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• 2012

Since the Free Trade Agreements (FTAs) with Chile, the EU, and the U.S., Korean agricultural produce markets have turned into a fierce competition landscape. Under these competitive circumstances, marketing is critical. The objective of the research presented herein is to understand the characteristics of customer preferences after locating trends of purchased items. So This research establishes sustainable strategies for Korean agricultural produce. This investigation used market-basket analysis techniques and panel data for its research. Market-basket analysis is a technique which attempts to find groups of items that are commonly found together. The results show that, for one year, processed food using wheat, processed marine products, and pork are commonly bought together and that yogurt and milk also are bought together. The characteristics of customers buying these items are 44 years old and live in a four-person household with two children. These customers do not live with their parents.