• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.706-712
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• 2015

These days, much information is provided as a list of summaries through mobile services. In this regard, users consume information in which they are interested by observing the list and not by expressing their interest explicitly or implicitly through rating content or clicking links. Therefore, to appropriately model a user's interest, it is necessary to detect latent interest content. In this study, we propose a method for reasoning latent interest of a user by analyzing mobile content consumption logs of the user. Specifically, since erroneous reasoning will drastically degrade service quality, a unanimity ensemble method is adopted to maximize precision. In this method, an item is determined as the subject of latent interest only when multiple classifiers considering various aspects of the log unanimously agree. Accurate reasoning of latent interest will contribute to enhancing the quality of personalized services such as interest-based recommendation systems.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.463-482
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• 1994

In Bayesian analysis of randomized response models, the likelihood function does not combine tractably with typical priors for the parameters of interest, causing computational difficulties in posterior analysis of the parameters of interest. In this article, the difficulties are solved by introducing appropriate latent variables to the model and using the Gibbs sampling algorithm.

• The Mathematical Education
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• v.63 no.1
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• pp.19-33
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• 2024

This study investigates longitudinal patterns in middle school students' mathematics interest and achievement using panel data from the 4th to 6th year of the Gyeonggi Education Panel Study. Results from the multivariate growth mixture model confirmed the existence of heterogeneous characteristics in the longitudinal trajectory of students' mathematics interest and achievement. Students were classified into four latent classes: a low-level class with weak interest and achievement, a high-level class with strong interest and achievement, a middlelevel-increasing class where interest and achievement rise with grade, and a middle-level-decreasing class where interest and achievement decline with grade. Each class exhibited distinct patterns in the change of interest and achievement. Moreover, an examination of the correlation between intercepts and slopes in the multivariate growth mixture model reveals a positive association between interest and achievement with respect to their initial values and growth rates. We further explore predictive variables influencing latent class assignment. The results indicated that students' educational ambition and time spent on private education positively affect mathematics interest and achievement, and the influence of prior learning varies based on its intensity. The perceived instruction method significantly impacts latent class assignment: teacher-centered instruction increases the likelihood of belonging to higher-level classes, while learner-centered instruction increases the likelihood of belonging to lower-level classes. This study has significant implications as it presents a new method for analyzing the longitudinal patterns of students' characteristics in mathematics education through the application of the multivariate growth mixture model.

• Journal of The Korean Association For Science Education
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• v.31 no.6
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• pp.876-886
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• 2011

This study was carried out to investigate the difference of gender of academic self-efficacy, external motivation, interest and science achievement for high school students of Korea and to verify the structural relationship among these variables using PISA 2006 data. The major findings of this study are as follows. According to Multi-group analysis, Latent means analysis (LMA), where boys were used as the reference group, girls showed lower latent mean values on the academic self-efficacy, extrinsic motivation and interest. Academic self-efficacy was found to have a greater effect on achievement compared to external motivation and interest. According to structural equation modeling (SEM) analysis, academic self-efficacy and extrinsic motivation affected interest. Academic selfefficacy, external motivation, and interest affected science achievement. Lastly, interest mediated academic selfefficacy and external motivation on science achievement.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.37-54
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• 2010

The information system that preserves and presents information collections, records, processes, retrievals, is applied in various fields recently and is supporting man's many activities. Conventional information systems are based on the reactive interaction model. Such reactive systems respond to only specific instructions, i.e. the defined commands, from the user. To go beyond the reactive interaction, it is necessary that the interactive dynamic interaction based information system which understands human's action and intention autonomously and then provides sensible information adapted to the user. Therefore, we propose a Gaze Mirroring-based intelligent information system for making user's latent interest using the internal state estimation methods based on the interactive dynamic interaction. Then, the proposed Gaze Mirroring method is that an anthropomorphic agent(avatar) actively established the joint attention with the user by imitating user's eye-gaze behavior. We verify that the Gaze Mirroring can elicit the user's behavior reflecting the latent interestand contribute to improving the accuracy of interest estimation. We also have confidence that the Gaze Mirroring promotes the self-awareness of interest. Such a Gaze Mirroring-based intelligent information system also provides suitable information to user by making user's latent interest using the internal state estimation.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.173-191
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• 2017

This study develops a new type of latent class analysis (LCA) in order to explain the associations between one latent variable and several other categorical latent variables. Our model postulates that the prevalence of the latent variable of interest is affected by another latent variable composed of other several latent variables. For the parameter estimation, we propose deterministic annealing EM (DAEM) to deal with local maxima problem in the proposed model. We perform simulation study to demonstrate how DAEM can find the set of parameter estimates at the global maximum of the likelihood over the repeated samples. We apply the proposed LCA model in an investigation of the effect of and joint patterns for drug-using behavior to violent behavior among US high school male students using data from the Youth Risk Behavior Surveillance System 2015. Considering the age of male adolescents as a covariate influencing violent behavior, we identified three classes of violent behavior and three classes of drug-using behavior. We also discovered that the prevalence of violent behavior is affected by the type of drug used for drug-using behavior.

• Journal of the Korean Society for information Management
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• v.32 no.3
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• pp.397-412
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• 2015

The main goal of this study is to investigate how to route a question to some relevant users who have interest in the topic of the question based on users' topic interest. In order to assess users' topic interest, archived question-answer pairs in the community were used to identify latent topics in the chosen categories using LDA. Then, these topic models were used to identify users' topic interest. Furthermore, the topics of newly submitted questions were analyzed using the topic models in order to recommend relevant answerers to the question. This study introduces the process of topic modeling to investigate relevant users based on their topic interest.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.226-236
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• 2021

The purpose of this study is to analyze the type of latent profile for general high school students' subject selection criteria and to identify the characteristics of the latent class. The survey data of 1072 general high school students (male; 648, female; 424) in G city, Jeollabuk-do and the scale composed of 8 sub-factors: 'SAT orientation', 'academic achievement', 'ability orientation', 'pursuit of interest', 'teacher orientation', 'career development', 'others' recommendation', and 'subject availability' were used for latent profile analysis and cross-analysis between potential layers. As a result of the analysis, high school students' perceptions of subject selection were classified into four latent profiles. The four groups were named 'High Perception Type', 'Low Perception Type', 'Self-Directed Type', and 'Stability-Oriented Type' according to their types. It was found that there was a difference between the latent classes in the importance and performance level of the subject selection criteria. These results can help identify the subject selection tendencies of latent groups in the operation of the 2015 revised curriculum and the 2025 high school credit system that emphasizes the student-centered course selection curriculum and they can also provide customized course selection guidance considering individual differences.

• Journal of Science Education
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• v.33 no.1
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• pp.100-110
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• 2009

This study analyzes the factors influencing interest on scientific subject and its change in Korean youth by using a sample from KEEP(Korea Education and Employment Panel 1-4) data. The results are as follows: First, the interest on scientific subject of Korean youth show quadratic curve. Also, the interrelationship between intercept and slope of subject interest is -.205 but it is not statistically significant Second, analysis of Latent Growth Models shows that self-esteem, academic achievement, school culture/climates and high school tracks are found to be a statistically significant factor on the intercept of subject interest These findings indicate that the interest on scientific subject of the Korean youth show a quadratic curve and various factors such as self-esteem, academic achievement and school culture/climates are much more influential on it.

• Asian Journal for Public Opinion Research
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• v.10 no.1
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• pp.4-22
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• 2022

The purpose of this study is to explore the structure of social discourse on aging in Korea by analyzing newspaper articles on aging. The analysis is composed of three steps: first, data collection and preprocessing; second, identifying the latent topics; and third, observing yearly dynamics of topics. In total, 1,472 newspaper articles that included the word "aging" within the title were collected from 10 major newspapers between 2006 and 2019. The underlying topic structure was analyzed using Latent Dirichlet Allocation (LDA), a topic modeling method widely adopted by text mining academics and researchers. Seven latent topics were generated from the LDA model, defined as social issues, death, private insurance, economic growth, national debt, labor market innovation, and income security. The topic loadings demonstrated a clear increase in public interest on topics such as national debt and labor market innovation in recent years. This study concludes that media discourse on aging has shifted towards more productivity and efficiency related issues, requiring older people to be productive citizens. Such subjectivation connotes a decreased role of the government and society by shifting the responsibility to individuals not being able to adapt successfully as productive citizens within the labor market.