• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.147-163
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• 2016

Gender information of a smart device user is essential to provide personalized services, and multi-modal data obtained from the device is useful for predicting the gender of the user. However, the method for utilizing each of the multi-modal data for gender prediction differs according to the characteristics of the data. Therefore, in this study, an ensemble method for predicting the gender of a smart device user by using three classifiers that have text, application, and acceleration data as inputs, respectively, is proposed. To alleviate privacy issues that occur when text data generated in a smart device are sent outside, a classification method which scans smart device text data only on the device and classifies the gender of the user by matching text data with predefined sets of word. An application based classifier assigns gender labels to executed applications and predicts gender of the user by comparing the label ratio. Acceleration data is used with Support Vector Machine to classify user gender. The proposed method was evaluated by using the actual smart device log data collected from an Android application. The experimental results showed that the proposed method outperformed the compared methods.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.29-37
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• 2018

This study intends to derive play attribute words to describe the nature of play by analyzing the correlation between play facilities and play attribute words. To investigate play attributes at playing facilities and supplement areas of weakness can provide a balanced play environment. Play attributes words were compiled via a literature review and the importance of each play attributes word was surveyed by experts. The keywords explaining play derived from news articles and references are defined as play attributes words. These words were classified into six broad categories and twenty-six sub-categories. The importance of major play attribute words show: Communication (0.268%) > Imagination (0.201%) > Amusement (0.190%) > Development (0.167%) > Learning (0.108%) > Intelligence (0.067%). Experts have recognized the most important elements are communication and imagination. Each play attribute associated with an amusement facility was separately identified in the amusement facilities installed in 114 children's parks in Seoul. Of the play attribute words, the amusement facilities at Seoul's Children's Park reflected a high frequency in 'development'. Furthermore, the importance of major playing attribute words such as 'Communication' and 'Imagination' were not fully reflected in cognitive play facilities. Therefore, it was judged that there is a need to actively introduce these attributes. This study proposed future improvements by determining weaknesses of amusement facilities in children's parks and analyzing the features and functions of play so as to suggest future improvements.

• Communications of Mathematical Education
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• v.29 no.3
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• pp.391-421
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• 2015

The scientific technology developed rapidly and the internet became more popular, also, the world became interactive with one another and the word 'Global' became popular and built a new paradigm. As the development of the society, the ideal criteria for the competent student changed. Consequently, the attention for the globalized education increased. From the points of view of mathematical education, it became a important task to be prepared for international competitiveness for korean talented students. For theses reasons, this article analyzes the characteristics of IBDP and its textbook, which is an international official curriculum and one of the actualizing method for internalization Korean high school curriculum and text book, specifically, focusing on algebra part. Especially, Korean curriculum textbooks and the Mathematical Higher Level textbooks of IBDP was compared and analyzed. As a result, the depth and range of the content, standard level of the question, methods being used to explain the concept, type of questions as well as teaching - learning method were analyzed and in each chapter of the algebra we give meaningful result and proposed discussion.

• Archives of design research
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• no.18
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• pp.113-121
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• 1996

Persuasion is one of the attractive channels to enhance the relation between markerters and consumers and deliver the true communication on products to the consumers. This arctic tried to examine the symbolic meaning system as a way of maximizing the visual communicational effect of persuasion, the efforts of marketers who are trying to utilize the psychology of the mass that consume the symbol rather than products and the symbol system as a mean of propaganda were analyzed as well. People in modern age, in general, place more value on the emotional assoessibility than the efficiency of the product, As a result, the ways of expression of propaganda approaching the mass are in the process of gradual change, which was another theme this article tried to explore. Ames sied that the human preoeption has a tendency to perceive things in some organized pattern, which can be applied to even untransparable and meaningless image. Human beings don't perceive what there is but what, thery believe there to be, and his peroeption are channelized by the opportunity of the past, his peroeption are channelized by the opportunity of the past, his experience of the environment, and the history of learning. To say another word, people not only recognize the objective form but also accept the inside meaning of the visual object. Their reponse to the visual object, therefore, include personal cognition, judgment, and attitued. The communication in visual design reveals the culture, society, and art in a complex symbol, and make synthetic cultural interpretation possible. It's pretty attractive, effective, and reasonable method to use symbolic meaning system as a way of persuasion. It is because communication means whole process from receiving and delivering the information and message to making common meaning system, to measuring the effect of the behavior change.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.511-522
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• 2014

During the development of the software, a variety of bugs are reported. Several bug tracking systems, such as, Bugzilla, MantisBT, Trac, JIRA, are used to deal with reported bug information in many open source development projects. Bug reports in bug tracking system would be triaged to manage bugs and determine developer who is responsible for resolving the bug report. As the size of the software is increasingly growing and bug reports tend to be duplicated, bug triage becomes more and more complex and difficult. In this paper, we present an approach to assign bug reports to appropriate developers, which is a main part of bug triage task. At first, words which have been included the resolved bug reports are classified according to each developer. Second, words in newly bug reports are selected. After first and second steps, vectors whose items are the selected words are generated. At the third step, TF-IDF(Term frequency - Inverse document frequency) of the each selected words are computed, which is the weight value of each vector item. Finally, the developers are recommended based on the similarity between the developer's word vector and the vector of new bug report. We conducted an experiment on Eclipse JDT and CDT project to show the applicability of the proposed approach. We also compared the proposed approach with an existing study which is based on machine learning. The experimental results show that the proposed approach is superior to existing method.

• Korean Journal of Cognitive Science
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• v.23 no.4
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• pp.425-455
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• 2012

Multi-dimensional verbal short-term memory mechanisms are largely divided into the phonological channel and the lexical-semantic channel. The former is called phonological short-term memory and the latter is called semantic short-term memory. Phonological short-term memory is further segmented into the phonological input buffer and the phonological output buffer. In this study, the language performance of each of three patients with similar levels of conduction aphasia was analyzed in terms of multi-dimensional verbal short-term memory. To this end, three patients with conduction aphasia were instructed to perform four different aspects of language tasks that are spontaneous speaking, repetition, spontaneous writing, and dictation in both word and sentence level. Moreover, the patients' phonological memories and semantic short-term memories were evaluated using digit span tests and verbal learning tests. As a result, the three subjects exhibited various types of performances and error responses in the four aspects of language tests, and the short-term memory tests also did not produce identical results. The language performance of three patients with conduction aphasia can be explained according to whether the defects occurred in the semantic short-term memory, phonological input buffer and/or phonological output buffer. In this study, the relations between language and multi-dimensional verbal short-term memory were discussed based on the results of language tests and short-term memory tests in patients with conduction aphasia.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.631-638
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• 2015

The purpose of this study is to provide developmental direction of medical education by analysing graduate medical school student's perception structure about 'good doctor' and the difference between graduate medical school student's perception structure about 'good doctor' before and after clerkship. Subject of study is medical students in 1st~4th year. NetMiner 4.0 program, which is social network analysis, was used to analyse. Many of the words that students used to describe good doctor were similar. But especially lots of times they used 'patient', 'treatment', 'competence', 'heart' and a word 'patient' showed highest degree centrality. Higher density of network and mean degree centrality were shown in students who experienced clerkship. 'Diagnosis and treatment', 'medical communication', 'attitudes to patients', 'medical knowledge', 'basic competence' these 5 groups were shown in network of students before and after clerkship in common. In the case of students after clerkship, 'lifelong learning ' groups have been added, so were the 6 groups. Considering the fact that social responsibility, professionalism, medical humanities are emphasized in recent medical education, students have lack of perception structure about good doctor, therefore education of this area needs to be strengthened.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.151-166
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• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.115-124
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• 2010

In the beginning brain waves were used for monkeys to control robot arm with neural activity. In recent years there are research that measured brain waves are used for the control of programs which monitor the progression of dementia or enhance of attention in children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD). Moreover, low-price devices that can be used as a game control interface have become available. One of the problems associated with control using brain waves is that the mean amplitude, mean wavelength, and mean vibrational frequency of the brain waves differ from individual to individual. This paper attempts to propose a method to normalize measured brain waves using normal distribution and calculate the waveforms that can be used in controlling games. For this, a framework in which brain waves are converted in seven stages has been suggested. In addition, the estimation process in each stage has been described. In an experiment the waveforms of two subjects have been compared using the proposed method in the BCI English word learning program. The level of similarity between two subjects' waveforms has been compared with correlation coefficient. When the proposed method was applied, both meditation and concentration increased by 13% and 8%, respectively. Because the proposed regularization method is converted into a waveform fit for control functions by reducing personal characteristics reflected in the brain waves, it is fitting for application programs such as games.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.13-33
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• 2020

This study proposes a Korean sentimental analysis algorithm that utilizes a letter-unit embedding and convolutional neural networks. Sentimental analysis is a natural language processing technique for subjective data analysis, such as a person's attitude, opinion, and propensity, as shown in the text. Recently, Korean sentimental analysis research has been steadily increased. However, it has failed to use a general-purpose sentimental dictionary and has built-up and used its own sentimental dictionary in each field. The problem with this phenomenon is that it does not conform to the characteristics of Korean. In this study, we have developed a model for analyzing emotions by producing syllable vectors based on the onset, peak, and coda, excluding morphology analysis during the emotional analysis procedure. As a result, we were able to minimize the problem of word learning and the problem of unregistered words, and the accuracy of the model was 88%. The model is less influenced by the unstructured nature of the input data and allows for polarized classification according to the context of the text. We hope that through this developed model will be easier for non-experts who wish to perform Korean sentimental analysis.