• Asia Marketing Journal
• /
• v.10 no.2
• /
• pp.125-151
• /
• 2008

Both companies and consumers are highly interested in on-line customer reviews which enable consumers to share their experience and knowledge about products. In this study, after classifying real reviews into context units and deriving categories, we analyzed differences between categories based on channel(manufacturers' homepage/ shopping mall), product attribute(search/experience) and price(high/low). The method to derive categories is based on roughly adopting constructs of ACSI model and elaborate and repetitive classification of real reviews. We set up the classification category with 3 levels. Level 1 consists of product and service, level 2 consists of function, design, price, purchase motive, suggestion/user-tip and recommendation/repurchase in product and AS/up-grade and delivery/others in service and level 3 is composed of details of level 2 of category. We could find remarkable differences between channels in all 8 items of level 2 of category. As the number of context units in homepage is more than in shopping mall, we found reviews in homepage is more concrete. Moreover, overall satisfaction in review was higher at homepage's. Also, in product attribute dimension, we found different patterns of reviews in design, purchase motive, suggestion/user-tip, recommendation/repurchase, AS/up-grade and delivery/others and no difference in overall customer's satisfaction. In price dimension, we found differences between high and low price in design, price and AS/up-grade and no difference in overall customer's satisfaction.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.109-130
• /
• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Korean Home Economics Education Association
• /
• v.19 no.4
• /
• pp.17-36
• /
• 2007

The purpose of this study was to develop health belief model based various milk education program as print education media and apply to elementary, middle, and high schools. The subjects were 432 students(124 elementary, 122 middle, 186 high school students). We designed one group pretest-posttest study model. The data were obtained from pre and post-study with self-administered questionnaires. Before applying this education program, we evaluated the degree of awareness on milk. Their awareness on milk was very low, 35.5% lower elementary, 32.7% higher elementary, 52.5% middle, and 54.3% high school students were answered they don't know the milk well. After they had implemented milk education program, their recognition on milk had changed that milk is nutritious as supplementary food. And their reasons for drinking milk were also changed that 'they want to eat it' in elementary school students, 'they want to be healthier' in middle school students, and 'they want to be taller' in high school students. Their nutrition knowledge score showed a significant increase(p<0.05). As a results. milk nutrition education has improved nutrition knowledge and recognition on milk in elementary, middle, and high school students. To improve their milk eating behaviors, nutrition education programs will have to be continued.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.253-266
• /
• 2018

This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.

• The Journal of Korean Association of Computer Education
• /
• v.17 no.2
• /
• pp.11-19
• /
• 2014

Presently the instructional model for internet ethics education is modeled after the integrated morality. The model is based on the assumption that ethical awareness will lead to ethical activities which is based on the theory that cognition is correlated to the behavioral domains. But the side effects of the information society in the cyber space increased even when the education for the awareness of ethics in the cyber space has been taught more aggressively than before. In this study, the relation of the cognition for information ethics and the ethical behavior in the cyber space was analyzed in order to find out the implications for the effective internet ethics education model. The tools used are the 'DIT (Defining Issues Test)' to measure the behavioral ability in the physical world, the Information Ethics Judgment to measure the behavioral ability in the cyber space, and the self diagnostic tool of 'Internet ethics awareness' to measure the level of cognitive knowledge for internet ethics. The correlation of three measures was analyzed. The results were college students' levels of ethics from three tools from are considerably low. Moral judgement and information ethics judgement were not correlated which means that the behavior in the physical world was not necessarily correlated to the behavior in the cyber space. The three measurements were not statistically significantly correlated. Therefore the cognitive awareness for the information ethics were not necessarily correlated to the ethical behavior in the cyber space. Ethical cognition and the moral behavior need to be taught with equal emphasis as they do not have strong correlation.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.6
• /
• pp.78-83
• /
• 2020

The information and knowledge of modern society in the 2lst century is changing rapidly. Based on this social change, the ministry of education introduced STEAM (Science Technology Engineering Art Music) in 2011 to foster creative convergence talents. Therefore, this study is based on the PBL model that learners participate in the class voluntarily to develop appropriate talents in the 21st century. The combined subjects were English, which is the world's official language, and Science, which is found in almost all the fields with the development of the 4th industrial revolution. As a result, learners could define the problems and solutions during the English class and take part in the group activity actively to obtain the problems and solutions of environmental pollution during the Science class. Through this, learners answered that they had a great understanding of learning (86%), high motivation for learning (100%), improved self-confidence (100%), and improved collaboration and creativity (100%). Unfortunately, this study does not progress actively due to the entrance exams, which still require accurate answers rather than the necessity and effectiveness of convergence education. To foster talents suitable for the present age, more active research should be applied to a range of educational sites.

• Journal of Gifted/Talented Education
• /
• v.27 no.1
• /
• pp.97-118
• /
• 2017

This paper aims to provide reference model for directions and objectives of Software(SW) gifted education. In order to achieve the goals introduced above, we conducted the research in the following steps. First, we selected the concept of ICT-based creative talented person as a base model to establish the concept of SW gifted person. The selected base model composed three core competencies which were 'knowledge and technology competencies', 'synthesizing and creativity competencies', and 'personality competencies'. Second, we developed survey tools, like questionnaires, to investigate participant's recognition of SW gifted person. The survey tools composed three components 'computational thinking', 'entrepreneurship', and 'social responsibility'. Each of the components composed seven elements. Third, after selecting the opinion poll participants as an elementary school teacher, we surveyed opinion polling. By selecting an elementary school teacher as the opinion poll participants, we wanted to identify theirs ' opinions which are thought to be the starting point for gifted education. To survey we developed on-line survey system by using Google functions. Fourth, we analyzed the collected opinion data. To identify we summarized and synthesized participant's opinions that average values and agreement level by using frequency analysis. Also, in order to compare opinions that average values and agreement level based on whether or not participant's various experiences and competencies we computed t-value, F-value, and ${\chi}^2$ verification.

• The Journal of Society for e-Business Studies
• /
• v.11 no.4
• /
• pp.1-20
• /
• 2006

Many government offices have been proceeding a development of Enterprise Architecture(EA) according to apply Government-wide Enterprise Architecture'. Each office and working-level officials have had a hard time because of no guides related to a EA development method such as the Framework, Standards, Principle, Reference Model, Etc. This paper propose a method for developing e-Government Enterprise Architecture considered a characteristic of public institutes through analyzing existing cases. The method for development e-Government EA includes the EA Performance Management Model to monitor objectively each office's long-term business promotion because the e-Government EA development is a job of long duration and cooperation with many institutes. This method also combines the EA Change Management Activities for the officials to improve general knowledge about EA's idea and EA's value, etc. We show the EA case study of the Ministry of Government Administration and Home Affairs to demonstrate feasibility of our approach. As a result, public offices will carry out their BPR(Business Process Re-engineering) and ISP(Information Strategy Planning) more efficiently based on this EA development method.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.10
• /
• pp.6041-6048
• /
• 2013

Background: Japanese women in their 40s or older have been encouraged to attend breast cancer screening. However, the breast cancer screening rate in Japan is not as high as in Europe and the United States. The aim of this study was to identify psychological and personal characteristics of women concerning their participation in breast cancer screening using the Health Belief Model (HBM). In addition, the attributes of screening more easily accepted by participants were analyzed by conjoint analysis. Materials and Methods: In this cross sectional study of 3,200 age 20-69 women, data were collected by an anonymous questionnaire. Questions were based on HBM and personal characteristics, and included attitudes on hypothetical screening attributes. Data of women aged 40-69 were analyzed by logistic regression and conjoint analysis to clarify the factors affecting their participation in breast cancer screening. Results: Among responses collected from 1,280 women of age 20-69, the replies of 993 women of age 40-69 were used in the analysis. Regarding the psychological characteristics based on HBM, the odds ratios were significantly higher in "importance of cancer screening" (95%CI: 1.21-2.47) and "benefits of cancer screening" (95%CI: 1.09-2.49), whereas the odds ratio was significantly lower in "barriers to participation before cancer screening" (95%CI: 0.27-0.51). Conjoint analysis revealed that the respondents, overall, preferred screening to be low cost and by female staff members. Furthermore, it was also clarified that attributes of screening dominant in decision-making were influenced by the employment status and the type of medical insurance of the women. Conclusions: In order to increase participation in breast cancer screening, it is necessary to disseminate accurate knowledge on cancer screening and to reduce barriers to participation. In addition, the attributes of screening more easily accepted were inexpensive, provided by female staff, executed in a hospital and finished in a short time.

• The KIPS Transactions:PartD
• /
• v.13D no.6 s.109
• /
• pp.823-832
• /
• 2006

The Purpose of Similarity(Reproduction) Degree Appraisal is to determine the equality or similarity between two programs and it is a system that presents the technical grounds of judgment which is necessary to support the resolution of software intellectual property rights through expert eyes. The most important things in proceeding software appraisal are not to make too much of expert's own subjective judgment and to acquire the accurate-appraisal results. However, up to now standard research and development for its systematic techniques are not properly made out and as different expert as each one could approach in a thousand different ways, even the techniques for software appraisal types have not exactly been presented yet. Moreover, in the analyzing results of all the appraisal cases finished before, through a practical way, we blow that there are some damages on objectivity and accuracy in some parts of the appraisal results owing to the problems of existing appraisal procedures and techniques or lack of expert's professional knowledge. In this paper we present the model for the standardization of software-similarity-appraisal techniques and objective-evaluation methods for decreasing a tolerance that could make different results according to each expert in the same-evaluation points. Especially, it analyzes and evaluates the techniques from various points of view concerning the standard appraisal process, setting a range of appraisal, setting appraisal domains and items in detail, based on unit processes, setting the weight of each object to be appraised, and the degree of logical and physical similarity, based on effective solutions to practical problems of existing appraisal techniques and their objective and quantitative standardization. Consequently, we believe that the model for the standardization of software-similarity-appraisal techniques will minimizes the possibility of mistakes due to an expert's subjective judgment as well as it will offer a tool for improving objectivity and reliability of the appraisal results.