• Journal of Information Processing Systems
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• v.15 no.1
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• pp.127-136
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• 2019

User-based and item-based approaches have been developed as the solutions of the movie recommendation problem. However, the user-based approach is faced with the problem of sparsity, and the item-based approach is faced with the problem of not reflecting users' preferences. In order to solve these problems, there is a research on the combination of the two methods using the concept of similarity. In reality, it is not free from the problem of sparsity, since it has a lot of parameters to be calculated. In this study, we propose a combining method that simplifies the combination equation of prior study. This method is relatively free from the problem of sparsity, since it has less parameters to be calculated. Thus, it can get more accurate results by reflecting the users rating to calculate the parameters. It is very fast to predict new movie ratings as well. In experiments for the proposed method, the initial error is large, but the performance gets quickly stabilized after. In addition, it showed about 6% lower average error rate than the existing method using similarity.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.96-104
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• 2020

As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.1010-1014
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• 2010

Article-related product recommender system is an emerging e-commerce service which recommends items based on association in contexts between items and articles. Current services recommend based on the similarity between tags of articles and items, which is deficient not only due to the high cost in manual tagging but also low accuracies in recommendation. As a component of novel article-related item recommender system, we propose a new method for tagging item images based on pre-defined categories. We suggest a hypernetwork-based algorithm for learning association between images, which is represented by visual words, and categories of products. Learned hypernetwork are used to assign multiple tags to unlabeled item images. We show the ability of our method with a product set of real-world online shopping-mall including 1,251 product images with 10 categories. Experimental results not only show that the proposed method has competitive tagging performance compared with other classifiers but also present that the proposed multi-tagging method based on hypernetworks improves the accuracy of tagging.

• Journal of The Korean Association For Science Education
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• v.22 no.1
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• pp.122-131
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• 2002

Recently, performance assessment that makes growing use of free response items in a large scale assessment has been emphasized. This study is an empirical examination of the effectiveness of free response items in comparison with multiple choice items. Using the information function in Item Response Theory (IRT) framework, item information of free response items and multiple-choice items from the Third International Mathematics and Science Study-Repeat (TlMSS-R) were obtained. Test information of the whole science area as well as each area of science contents was computed. On average, free response items yielded more information than multiple choice items, especially in earth science, physics, chemistry, and life science. This study also showed that free response items were appropriate for students in high science ability. Also, free response items estimated students' science ability more accurately than multiple choice items with smaller number of free response items.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.309-321
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• 2014

Recently, due to the advent of ubiquitous computing and the spread of intelligent portable device such as smart phone, iPad and PDA has been amplified, a variety of services and the amount of information has also increased fastly. It is becoming a part of our common life style that the demands for enjoying the wireless internet are increasing anytime or anyplace without any restriction of time and place. And also, the demands for e-commerce and many different items on e-commerce and interesting of associated items are increasing. Existing collaborative filtering (CF), explicit method, can not only reflect exact attributes of item, but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, using a implicit method without onerous question and answer to the users, not used user's profile for rating to reduce customers' searching effort to find out the items with high purchasability, it is necessary for us to analyse the segmentation of customer and item based on customer data and purchase history data, which is able to reflect the attributes of the item in order to improve the accuracy of recommendation. We propose the method of recommendation system using association rule and weighted preference so as to consider many different items on e-commerce and to refect the profit/weight/importance of attributed of a item. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• IE interfaces
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• v.22 no.4
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• pp.368-375
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• 2009

This paper considers a two-stage supply system consisting of two make-to-stock facilities. The facility in the first stage produces a single type of component in anticipation of future demands from the market and the end item production while the facility in the second stage produces the end item in anticipation of future demands from the OEM customers. The facility in the first stage has the option of to accept or reject each incoming demand from the market. In this paper, we address the problem of how to control the exogenous component demand and how to manage the production of the end item and the component so as to maximize the system's profit subject to the system costs. In this paper, we present a heuristic policy that is the base-stock production policy combined with a linear switching curve for component demand control. Numerical study is implemented under different operating conditions of the system and it shows that the performance of the heuristic is very promising compared to that of the optimal policy for the Markov model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.1
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• pp.89-95
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• 2006

Planning distributed manufacturing logistics is one of main issues in supply chain management. This paper proposes a hybrid heuristic approach for the Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP) in supply chain network. MLCLSP corresponds to a mixed integer programming (MIP) problem. With integer variable solutions determined by heuristic search, this MIP problem becomes linear program (LP). By repeatedly solving the relaxed MIP problems with a heuristic search method in a hybrid manner, this proposed approach allocates finite manufacturing resources fur each distributed facilities and generates feasible production plans. Meta heuristic search algorithm is presented to solve the MIP problems. The experimental test evaluates the computational performance under a variety of problem scenarios.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.20-41
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• 1999

This study addresses the development of a quality measurement of information systems integration(SI) service. Several dimensions which affect on quality of systems integration service have been identified and tested. Also, a measurement tool(questionnaire) of the factors has been developed. To achieve above purpose, extensive literature review and in-depth interview with several SI managers and customers were used. We suggested the analysis framework including performance variables such as quality, customer satisfaction, intention of renewal contract, and contribution to better customer's information system and the quality factors as well. To verify the research framework, collected data from the survey was analyzed statistically. The data from 73 respondents was used for analysis. Consequently, we identified eight factors and developed a 41-item instrument with Likert 5 points to measure the quality of SI service. It was proved that the 41-item instrument suggested in this study was very useful to measure the performance of SI service such as quality and customer satisfaction. Also it was shown that the instrument measured intention of renewal contract and contribution of customer's information system well.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.145-152
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• 2020

When conducting a health screening, it is important to select the most appropriate hospitals for the screening items. There are various packages in the screening hospitals, and the screening items and price are very different for each package. In this paper, we provide a method of recommending the screening packages in consideration of the customer's preferences such as screening items and minimum matching ratio. First, after collecting package information of hospitals, information such as basic items and optional items in the package are extracted. Then, we determine whether the client's screening items exist in the basic item or optional item of the package and calculate the matching rate of the package. Finally, we recommend screening packages with the lowest price while meeting the minimum matching rate suggested by the client. For performance analysis, we implement a prototype for recommending screening packages and provide the experimental results. The performance analysis shows that the proposed approach provides a real-time response time and recommends appropriate packages.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.200-205
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• 2000

An economic process monitoring procedure is presented using a surrogate variable for the case where performance variable is dichotomous. Every item is inspected with a surrogate variable and determined whether it should be accepted or rejected. When an item is rejected, the previous number of consecutively accepted items is compared with a predetermined number r to decide whether there is a shift in fraction nonconforming or not. The conditional distribution of the surrogate variable given the performance variable is assumed to be normal. A cost model is constructed which includes costs of inspection, misclassification, illegal signal, undetected out-of-control state, and correction. Methods of finding the optimum number r and screening limit are provided. Numerical studies on the effects of cost coefficients are also performed.