• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.59-67
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• 1992

This paper deals with preventive replacements models for the item whose failures are dependent on their wear level. When measuring the item wear level is very costly, it may be economical to use substitutive characteristics that are correlated with the item wear level and relatively inexpensive to measure. In this paper, replacement policies based on such substitutive characteristics are proposed. The optimal level of substitutive characteristic to replace the item, which minimizes total cost, is obtained. Some numerical examples are also given.

• The Korea Journal of Herbology
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• v.37 no.2
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• pp.13-21
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• 2022

Objectives : The evaluation of academic achievement is pivotal for establishing accurate direction and adequate level of medical education. The purpose of this study was to firstly establish innovative item analysis technique of Item Response Theory (IRT) for analyzing multiple-choice test of herbology in the traditional Korean medicine education which has not been available for the difficulty of test theory and statistical calculation. Methods : The answers of 390 students (2012-2018) to the 14 item herbology test in college of Korean medicine were used for the item analysis. As for the multidimensional analysis of item characteristics, difficulty, discrimination, and guessing parameters along with item-total correlation and percentage of correct answer were calculated using Classical Test Theory (CTT) and IRT. Results : The validity parameters of strong and weak items were illustrated in multiple perspectives. There were 4 items with six acceptable index scores, and 5 items with only one acceptable index score. The item discrimination of IRT was found to have no significant correlation with difficulty and discrimination indices of CTT emphasizing attention of professionals of medical education as for the test credibility. Conclusion : The critical suggestions for the development, utilization and revision of test items in the e-learning and evidence-based Teaching era were made based on the results of item analysis using IRT. The current study would firstly provide foundation for upgrading the quality of Korean medicine education using test theory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5826-5841
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• 2019

In our previous research, we proposed a tag emotion-based item recommendation scheme. The ternary associations among users, items, and tags are described as a three-order tensor in order to capture the emotions in tags. The candidates for recommendation are created based on the latent semantics derived by a high-order singular value decomposition technique (HOSVD). However, the tensor is very sparse because the number of tagged items is smaller than the amount of all items. The previous research do not consider the previous behaviors of users and items. To mitigate the problems, in this paper, the item-based collaborative filtering scheme is used to build an extended data. We also apply the probabilistic ranking algorithm considering the user and item profiles to improve the recommendation performance. The proposed method is evaluated based on Movielens dataset, and the results show that our approach improves the performance compared to other methods.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.9-16
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• 2016

Collaborative filtering(CF) uses the purchase or item rating history of other users, but does not need additional properties or attributes of users and items. Hence CF is known th be the most successful recommendation technology. But conventional CF approach has some significant weakness, such as the new user problem. In this paper, we propose a approach using word embedding with skip-gram for learning distributed item representations. In particular, we show that this approach can be used to capture precise item for solving the "new user problem." The proposed approach has been tested on the Movielens databases. We compare the performance of the user based CF, item based CF and our approach by observing the change of recommendation results according to the different number of item rating information. The experimental results shows the improvement in our approach in measuring the precision applied to new user problem situations.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.135-141
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• 2019

Collaborative filtering algorithms often encounter data sparsity issues. To overcome this issue, auxiliary information of relevant items is analyzed and an item attribute matrix is derived. In this study, we combine the user-item attribute preference with the traditional similarity calculation method to develop an improved similarity calculation approach and use weights to control the importance of these two elements. A collaborative filtering algorithm based on user-item attribute preference is proposed. The experimental results show that the performance of the recommender system is the most optimal when the weight of traditional similarity is equal to that of user-item attribute preference similarity. Although the rating-matrix is sparse, better recommendation results can be obtained by adding a suitable proportion of user-item attribute preference similarity. Moreover, the mean absolute error of the proposed approach is less than that of two traditional collaborative filtering algorithms.

• The Mathematical Education
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• v.46 no.4
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• pp.407-421
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• 2007

The purpose of this study is to identify the item characteristics that are supposed to affect item difficulty and to estimate the regression equations for predicting item difficulty of mathematics in the College Scholastic Ability Test(CSAT). We selected six variables related to item characteristics based on learning theories: contents, cognitive domain, novelty, item type, number of concepts, and the amount of computation. With data of the CSAT mathematics test administered in 2004-2006, item difficulty was regressed on the six variables, the location of an item, and the item writer's judgment on difficulty. The novelty of an item was found to be a statistically insignificant variable in explaining item difficulty. Four regression equations with different sets of independent variables could explain $70%{\sim}80%$ of the item difficulty variance and were validated as predicting item difficulty of the mock CSAT in 2006.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.3
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• pp.757-766
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• 2017

This study investigated not only the existence of differently functioned item due to gender but also domain. In this study, the randomly selected data of TIMSS 2007, which consist of 681 male and 646 women, were analyzed. To detect differently functioned items, this study employed Raju method. For Raju method, three-parameter logistic model was selected. Signed and unsigned area between two item characteristic curve were measured within the real ability range. An item which was detected commonly SA and UA area in Raju method was defined as a differently functioned item. As a result of this study, six items among twenty seven items of mathematics in the TIMSS 2007 were differently functioned item. Five items among those six items, were in favor of boys and one item was in favor of girls. Number, Geometric Shapes and Measures, and Applying were in favor of boys. but Data Display, Reasoning were in favor of girls. The conclusion of this study was summarized as existing differently functioned items in TIMSS 2007 and difference between favorable domain based gender. Finally, it is desirable to consider the differently functioned items by relating those item content for improving the test reliability of TIMSS 2007.

• Physical Therapy Korea
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• v.20 no.3
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• pp.89-99
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• 2013

The purposes of this study were: 1) to show the item difficulty hierarchy of walking/moving construct of the International Classification of Functioning, Disability and Health-Activity Measure (ICF-AM), 2) to evaluate the item-level psychometrics for model fit, 3) to describe the relevant physical activity defined by level of activity intensity expressed as Metabolic Equivalent of Tasks (MET), and 4) to explore what extent the empirical activity hierarchy of the ICF-AM is linked to the conceptual model based on the level of energy expenditure described as MET. One hundred and eight participants with lower extremity impairments were examined for the present study. A newly created activity measure, the ICF-AM using an item response theory (IRT) model and computer adaptive testing (CAT) method, has a construct on walking/moving construct. Based on the ICF category of walking and moving, the instrument comprised items corresponding to: walking short distances, walking long distances, walking on different surfaces, walking around objects, climbing, and running. The item difficulty hierarchy was created using Winstep software for 20 items. The Rasch analyses (1-parameter IRT model) were performed on participants with lower extremity injuries who completed the paper and pencil version of walking/moving construct of the ICF-AM. The classification of physical activity can also be performed by the use of METs that is often preferred to determine the level of physical activity. The empirical item hierarchy of walking, climbing, running activities of the ICF-AM instrument was similar to the conceptual activity hierarchy based on the METs. The empirically derived item difficulty hierarchy of the ICF-AM may be useful in developing MET-based activity measure questionnaires. In addition to convenience of applying items to questionnaires, implications of the finding could lead to the use of CAT method without sacrificing the objectivity of physiologic measures.

• ETRI Journal
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• v.46 no.2
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• pp.277-289
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• 2024

In this paper, we describe a neural network-based application that recommends multiple items using dialog context input and simultaneously outputs a response sentence. Further, we describe a multi-item recommendation by specifying it as a set of clothing recommendations. For this, a multimodal fusion approach that can process both cloth-related text and images is required. We also examine achieving the requirements of downstream models using a pretrained language model. Moreover, we propose a gate-based multimodal fusion and multiprompt learning based on a pretrained language model. Specifically, we propose an automatic evaluation technique to solve the one-to-many mapping problem of multi-item recommendations. A fashion-domain multimodal dataset based on Koreans is constructed and tested. Various experimental environment settings are verified using an automatic evaluation method. The results show that our proposed method can be used to obtain confidence scores for multi-item recommendation results, which is different from traditional accuracy evaluation.

• Korean Medical Education Review
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• v.16 no.1
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• pp.11-15
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• 2014

A number of medical schools in Korea have been using computer-based testing (CBT) for evaluating their students' scientific and/or clinical performance since the early 1990s. Introducing CBT to medical education would have several advantages: first, presenting figures and audio-video files of clinical content is simple with CBT, making it possible to evaluate medical students' competency with navigating more realistic clinical situations at minimum cost; second, CBT enables automatic item analysis and score reporting. To establish CBT, constructing an item bank with item parameters such as difficulty or discriminating parameters will be needed. To select more psychometrically sound items, analysis of the items according to item response theory is necessary. CBT has already been introduced in high stakes tests like the United States Medical Licensing Examination and the Medical Council of Canada Qualifying Examination. The National Health Personnel Examination Board in Korea is also planning to introduce a CBT-based version of the National Medical Examination soon. Thus all medical schools in Korea will need to introduce CBT and construct item banks to prepare their students for their licensing examinations and to measure the students' competency more accurately.