• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.29-63
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• 2014

This study attempted to reveal the characteristics of the Y generation, to derive the services of the next generation digital library, and to compare differences between the demands of the baby boom generation and the Y generation to some extent. As a result, first, it is shown that the digital device the Y generation uses the most, was a cell phone or smartphone, followed by desktop PC, notebook PC, and digital camera. Although there were some differences, the Y generation's use ratio of digital devices was substantially similar to the baby boomers'. Second, there was a significant difference between the Y generation and baby boom generation in terms of using digital services. While the Y generation used internet portals the most, the baby boom generation used e-mail service the most. Third, we surveyed the services which the Y generation and baby boom generation require for the next generation digital libraries, by grouping as follows: the cloud service, infinite creative space (maker space), big data, augmented reality, Google Glass, context-aware technologies, semantic services, SNS service, digital textbook service, RFID and QRCode service, library space configuration, a state-of-the-art display technology, and other innovative services. While the most demanded service by the Y generation was big data service, the baby boom generation most demanded digital textbook service.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.270-277
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• 2002

Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

• Journal of Korean Home Economics Education Association
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• v.19 no.2
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• pp.61-75
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• 2007

The method used in this descriptive study is the survey. The purpose of the study is to investigate performances of middle school home economics(HE) teachers regarding the HE subject. Respondents in this study were 177 HE teachers. Questionnaires from HE teachers were collected through e-mails. With the operation of the SPSS/Win (ver10.1) program, the analyses such as mean, standard deviation, frequencies, percents, t-test and ANOVA are done to see the relations between the related variables. The results of this study were as follows. First, the middle school HE teachers performed well above the standards in terms of planning, execution, and evaluation about self supervision related to HE. Second, the HE teachers collected materials for instruction by using literary (books) survey, Internet and mass media. They mainly focused on improving ways of "teaching and learning" and deepening the studies related to contents of textbooks. Third, the HE teachers used various ways to improve self supervision in the following order: mass media, literary (books) survey, participation in societies for researches, meetings, various training and field trip More than half of the middle school HE teachers proceeded to graduate schools, joined meetings for researches and had experiences of taking classes in private institutes. They also made a field trip once or twice a year and depended much on TV programs and education broadcasting programs as ways of improving their performances related to self supervision. While they were actively sharing information with their peer group, they made little effort at analyzing and evaluating their classes and utilizing expert group for their classes. The main problems as to self supervision were that only the half of the HE teachers responded that they were performing self supervision related to their classes well above the standards and the area where they heavily focused on has been "teaching and learning" and "the studies related to contents of textbooks". Therefore, to motivate incentives of the HE teachers for self supervision, meetings for researches should be activated and various training programs should be developed. In addition, government should give administrative and institutional support through a publication of books introducing detailed ways of self supervision and an establishment of centers and institutions for supporting self supervision.