• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.221-247
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• 2013

The purpose of the study is to investigate and analyze the categories of online bookstores and to propose improvements. For the study, the category conformity was compared among eight Korean online bookstores selected; the book classification on the categories was compared from them. The results show that the category conformity was high among online bookstores, but the book classification on the categories was different on the bookstores. ISBN contents classification codes for books might not help to classify the books on the categories. Thus, the study proposes a new publication category for the book classification on categories of online bookstores.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.145-152
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• 2015

We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.2
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• pp.287-304
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• 2016

This study examines the influence of product classification standards and structure on user perception as well as their attitude towards online shopping sites. The causal relationships of variables are also examined. The analysis was based on an online survey with 247 responses. Four types of internet shopping sites were developed and used as a stimulus. The results of the mean comparison analysis indicated that perceived variety, information overload, perceived shopping value and attitude towards the site varies significantly with product classification standards and structure. There was also of a marginally significant interaction between the classification standard and structure on perceived variety and information overload. The causal relationship analysis revealed that perceived variety positively influenced hedonic and utilitarian shopping value. However, information overload had a negative effect on hedonic and utilitarian shopping value. Both the hedonic and utilitarian shopping value positively influenced attitudes towards the sites. This study demonstrates that classification method influences customer perception and attitude. It offers interesting insights on a product classification method as a strategic tool for online shopping.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.147-165
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• 2023

New technologies representing the Fourth Industrial Revolution are already being realized in library services. There is not, however, active research on measures to increase work efficiency by introducing a new technology in the work of "classification" that is part of the traditional librarian jobs they should continue in the future. The Dewey Decimal Classification (DDC) has not issued a print version since 2018. This study analyzes cases of WebDewey, Classification Web, and UDC Online. The functions required for the development of the Korean Decimal Classification (KDC) web version were derived, and the final functions suitable for the development of the KDC web version were proposed through AHP analysis.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.291-300
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• 2020

Although the need for international online courses and the number of online learners has been rapidly increasing, the online class evaluation has been mostly relying on the quantitative survey analysis. So a more objective evaluation method has to be developed to more accurately assess online course satisfaction. This study highlights the benefits of using big data analysis from the bulletin board messages of online learning system as a method to evaluate the online courses. In fact, automatic classification technology is recognized as an important technology among big data analysis techniques. Our team applied this technique to evaluate the online courses. From the delphi analysis results, suggested method was concluded that the evaluation items and classification results are suitable for online course evaluation and applicable in schools or institutions. This study has confirmed that the rapidly accumulating big data analysis technology can be successfully applied to the education sector with the least change. It also diagnosed a meaningful possibility to expand the big data analysis for further application.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.31-32
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• 2011

• Journal of Korean Elementary Science Education
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• v.40 no.1
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• pp.66-80
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• 2021

This study is a case study that applies plant classification learning using machine learning to fourth graders in elementary school in online learning situations. In this study, a plant classification learning education program associated with 2015 revision science curriculum was developed by applying the Artificial Intelligence biological classification teaching Learning model. The study participants were 31 fourth graders who agreed to participate voluntarily. Plant classification learning using machine learning was applied six hours for three weeks. The results of this study are as follows. First, as a result of image analysis on artificial intelligence, participants were mainly aware of artificial intelligence as mechanical (27%), human (23%) and household goods (23%). Second, an artificial intelligence recognition survey by semantic discrimination found that artificial intelligence was recognized as smart, good, accurate, new, interesting, necessary, and diverse. Third, there was a difference between men and women in perception and emotion of artificial intelligence, and there was no difference in perception of the ability of artificial intelligence. Fourth, plant classification learning using machine learning in this study influenced changes in artificial intelligence perception. Fifth, plant classification learning using machine learning in this study had a positive effect on reasoning ability.

• Journal of Information Science Theory and Practice
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• v.3 no.4
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• pp.62-77
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• 2015

This paper describes qualities of a library classification system that are commonly discussed in the LIS tradition and literature, and explains such a system’s three main functions, namely knowledge mapping, information retrieval, and shelf arrangement. In this vein, the paper states the functional requirements of bibliographic classifications, which broadly are subject collocation and facilitation of browsing the collection. It explains with details the components of a library classification system and their functions. The major components are schedules, notations, and index. It also states their distinguished features, such as generalia class, form divisions, book numbers, and devices for number synthesis which are not required in a knowledge classification. It illustrates with examples from the WebDewey good examples of added features of an online library classification system. It emphasizes that institutional backup and a revision machinery are essential for a classification to survive and remain relevant in the print and e-environment.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.325-341
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• 2015

This paper describes the Tezpur University dataset of online handwritten Assamese characters. The online data acquisition process involves the capturing of data as the text is written on a digitizer with an electronic pen. A sensor picks up the pen-tip movements, as well as pen-up/pen-down switching. The dataset contains 8,235 isolated online handwritten Assamese characters. Preliminary results on the classification of online handwritten Assamese characters using the above dataset are presented in this paper. The use of the support vector machine classifier and the classification accuracy for three different feature vectors are explored in our research.

• The Journal of Information Systems
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• v.32 no.3
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• pp.133-150
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• 2023

Purpose This study aims to develop classification models using a decision tree algorithm to identify core keywords and rules influencing online consumer review evaluations for the robot vacuum cleaner on Amazon.com. The difference from previous studies is that we analyze core keywords that affect the evaluation results by dividing the subjects that evaluate online consumer reviews into self-evaluation (star ratings) and peer evaluation (helpfulness votes). We investigate whether the core keywords influencing star ratings and helpfulness votes vary across different products and whether there is a similarity in the core keywords related to star ratings or helpfulness votes across all products. Design/methodology/approach We used random under-sampling to balance the dataset. We progressively removed independent variables based on decreasing importance through backwards elimination to evaluate the classification model's performance. As a result, we identified classification models that best predict star ratings and helpfulness votes for each product's online consumer reviews. Findings We have identified that the core keywords influencing self-evaluation and peer evaluation vary across different products, and even for the same model or features, the core keywords are not consistent. Therefore, companies' producers and marketing managers need to analyze the core keywords of each product to highlight the advantages and prepare customized strategies that compensate for the shortcomings.