• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.155-164
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• 2016

For frequency pattern analysis of large databases, the new tree-based frequency pattern analysis algorithm which can compensate for the disadvantages of the Apriori method has been variously studied. In frequency pattern tree, the number of nodes is associated with memory allocation, but also affects memory resource consumption and processing speed of the growth. Therefore, reducing the number of nodes in the tree is very important in the frequency pattern mining. However, the absolute criteria which need to order the transaction items for construction frequency pattern tree has lowered the compression ratio of the tree nodes. But most of the frequency based tree construction methods adapted the absolute criteria. FP-tree is typically frequency pattern tree structure which is an extended prefix-tree structure for storing compressed frequent crucial information about frequent patterns. For construction the tree, all the frequent items in different transactions are sorted according to the absolute criteria, frequency descending order. CanTree also need to absolute criteria, canonical order, to construct the tree. In this paper, we proposed a novel frequency pattern tree construction method that does not use the absolute criteria, IRFP-tree algorithm. IRFP-tree(Intersection Rule based FP-tree). IRFP-tree is constituted with the new paradigm of the intersection rule without the use of the absolute criteria. It increased the compression ratio of the tree nodes, and reduced the tree construction time. Our method has the additional advantage that it provides incremental mining. The reported test result demonstrate the applicability and effectiveness of the proposed approach.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.69-85
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• 2006

Broadcast has been often used to disseminate the frequently requested data efficiently to a large volume of mobile clients over a single or multiple channels. Conventional concurrency control protocols for mobile transactions are not suitable for the wireless broadcast environments due to the limited bandwidth of the up-link communication channel. In wireless broadcast environments, the server often broadcast different data items with different frequency to incorporate the data access patterns of mobile transactions. The previously proposed concurrency control protocols for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. However, these protocols perform poorly when the data access pattern of update mobile transaction are not uniform but skewed. The update mobile transactions with skewed data access patterns will be frequently aborted and restarted due 4o the update conflict of the same data items with a high access frequency. In this paper, we propose an energy-efficient concurrence control protocol for mobile transactions with skewed data access as well as uniform data access patterns. Our protocol use a random back-off technique to avoid the frequent abort and restart of update mobile transactions. We present in-depth experimental analysis of our method by comparing it with existing concurrency control protocols. Our performance analysis show that it significantly decrease the average response time, the amount of upstream and downstream bandwidth usage over existing protocols.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.3
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• pp.283-288
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• 2005

A portable primary inductance standard set that includes a Maxwell-Wien bridge and a 10 mH standard inductor installed in a thermostat has been developed at KRISS. Two auxiliary resistance capacitance networks (analogous to a 'Wagner ground') provide excellent stability of the bridge balance and impose less strict requirements on the components of these networks. Removable capacitance and ac-dc resistance standards used in the bridge arms made it possible to reproduce 10 mH and 100 mH inductance values in the frequency range of 500 Hz to 3 kHz. From investigations of this standard and preliminary comparison with VNIIM (D. I. Mendeleyev Institute for Metrology), the results have demonstrated that the bridge can be used as a part of the transportable inductance standard with a measurement uncertainty within (1-3) $\mu$H/H at frequencies of 1 kHz and 1.6 kHz. The application of the bridge as a constituent part of the transportable standard gives us an opportunity to eliminate the influence of the standard inductors.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.45-61
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• 2008

Previous U-Commerce researches have dealt with the business support systems for traditional commerce space such as real world shopping malls. This paper investigates U-Commerce business models in service space. The McDonald's Touch-Order case is analyzed from business model perspective and the Media-Embedded Place business model is introduced as a U-Commerce business model for value creation in service space. The media-embedded place business model attaches auto-identification tags to tables or billboards, triggers commercial transaction through the tags, and shares the revenues and the incentives among the place owners and commerce/content providers. This paper analyzes its scenario and applications and illustrates the profitability analysis using so-called 'tag evaluation model'.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.359-368
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• 2014

Recently, to reflect the context between transactions, the intertransaction association rule mining has been study. In this study, we present two problems that is within intertransaction association rule mining method and suggest the methods to solve this problems. First, we suggest an algorithm to reflect changes on data between transactions. Second, we propose the method to solve the unfairly considered frequency of data when intertransactions is generate with transactions. We make more meaningful rules than previous researches. We present the experiment result with measured data from the marine environment.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.496-501
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• 2007

Recently, as MEMS and NEMS devices have been widely used in the various engineering applications, the characteristics of nanoscale systems are investigated in the limelight. However, as opposed to a macroscale system, the identification of the state of nanoscale systems is extremely hard because they can include only the order of $10^{3}\sim10^{5}$ molecules, which requires highly expensive and accurate experimental apparatus for an investigation. This limitations make the study on nanoscale system use computer simulations. Therefore, it is strongly required to identify the state of nanoscale system simulated in computer simulation. In these molecular dynamics(MD) study, we suggest that the potential energy of individual molecule can be used as criterion for defining the state of clusters or nanoscale systems. In addition, we compared the phase state from the potential energy with one from the radial distribution function(RDF) for verification. The comparison showed that the intermolecular potential energy can be used as a criteria distinguishing the phase state of nanoscale systems (This study will be published soon in the KSME transaction of the section B).

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.430-438
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• 2007

In the current RFID (Radio Frequency IDentification) middleware systems based on the EPCglobal standard, the tag data received by multiple readers are processed sequentially in FIFO (First In First Out) order. Considering the priority of RFID reader makes the RFID system more flexible and improve the data transaction throughput in the service environment where important tag data with high priority for a specific reader. In this study, we propose a new RFID middleware system architecture supporting priority service with the Buffer Management Component. Our proposals are compliant with the EPCglobal ALE (Application Level Events) standard interface for middleware systems and their clients. To verify the efficiency of this proposed system, simulation is used for evaluation.

• Knowledge Management Research
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• v.9 no.3
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• pp.59-76
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• 2008

Due to rapid increase in number of Internet users, the volume of domestic Internet shopping is expanding dramatically. Although the Internet shopping mall business is steadily growing, it has structural weakness, and in general, the business does not generate profit. In this context, this research identifies characteristics of the Internet shopping non-adopters, and suggests strategies to strengthen competitiveness of domestic Internet shopping malls and to create a new demand. Analysis of MCR data in 2007 showed that out of 4,298 respondents, 2,206 people adopted Internet shopping (51.3%). and 2,092 did not (48.7%). The survey measured 28 items regarding a consumption pattern and a lifestyle of the Internet users, and the analysis result showed that the pattern can be categorized in seven groups. Based on the analysis, the research suggests that the domestic Internet shopping malls adopt strategies to increase consumers' access frequency to tile Internet service, provide high-end goods, diversify transaction methods, make online shopping more convenient, cater to diversified consumer demands based on demographic data, provide price comparison more Internet shopping mails, and provide sufficient and useful information to consumers.

• Journal of Korean Academy of Nursing Administration
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• v.9 no.1
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• pp.31-40
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• 2003

Purposes : The purpose of this study is to analyze the correlation among Expectations, Performance-Perception, Willingness of reuse of hospital. Methods : The subjects of this study were 120 patients who were admitted in the hospitals over 1 week in Pusan. The data was collected by self-reporting questionnaires from Oct. 16th, to Nov. 5th, 2001. The data were analysed by SPSS/PC package using frequency, percentage, mean, standard deviation, Pearson's correlation coefficient. Results : The results were as follows; 1) The mean score of Expectation was 3 and over. The highest item was 'equal treatment' and the lowest was 'safety in transaction'. 2) The mean score of Performance-Perception was 4 and under. The highest item was 'nurse' attractive appearance' and the lowest was 'equal treatment', 'kindness and etiquette'. 3) The mean score of Willingness of reuse was 3.11. 4) There was a statistical significance of the difference between Expectations and Performance-Perception. The highest difference item was 'equal treatment', and then the lowest difference item was 'working environment arrangement/order'. 5) There were statistically significant positive correlation among Expectations, Performance-Perception, and Willingness of reuse. The highest correlation was 0.89 between Performance-Perception and Willingness of reuse. Conclusions : Nursing managers have to develop nurse training programs for improving of patient's performance perception on nursing service.