• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.141-166
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• 2018

Information technology improves the efficiency of humanities research. In humanities research, information technology can be used to analyze a given topic or document automatically, facilitate connections to other ideas, and increase our understanding of intellectual history. We suggest a method to identify and automatically analyze the relationships between arguments contained in unstructured data collected from humanities writings such as books, papers, and articles. Our method, which is called history mining, reveals influential relationships between arguments and the philosophers who present them. We utilize several classification algorithms, including a deep learning method. To verify the performance of the methodology proposed in this paper, empiricists and rationalism - related philosophers were collected from among the philosophical specimens and collected related writings or articles accessible on the internet. The performance of the classification algorithm was measured by Recall, Precision, F-Score and Elapsed Time. DNN, Random Forest, and Ensemble showed better performance than other algorithms. Using the selected classification algorithm, we classified rationalism or empiricism into the writings of specific philosophers, and generated the history map considering the philosopher's year of activity.

• Journal of Korean Home Economics Education Association
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• v.29 no.2
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• pp.23-39
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• 2017

The Purpose of this study is to present the basic data for selecting and improving the safety education contents which help practically middle school students through analysis of contents of safety education in 'field of home life' of 2009 revised middle school textbooks. The subjects of analysis are 12 types of middle school textbooks: in total 24 books written by 12 publishers in terms of the revised curriculum in 2009. The analysis criteria is developed by the researcher referring to preceding studies regarding safety education based on the seventh safety education standard presented by the Ministry of Education (2015). With such analysis criteria, all words related to the contents of the safety education of analysis criteria were extracted from each textbook, such as words directly mentioned as 'safety', words mean as 'psychological safety' and 'happy life', words related to 'attention', 'note', 'stability' etc. Under the analytic frame of safety education contents according to a home economics textbook, content analysis method was used for producing the frequency and percent of those words. The textbook analysis shows that the number of pages regarding safety education is 336.3 pages, as 9.8% in total 3,412 pages of 12 types of technology and home economics textbooks. As following the analysis of each textbook volume of the proportion in the contents related to safety education, 224.9 pages are on the first volume and 111.9 pages are on the second volume. As grades increase from year one to year three, the proportion of safety education in home economics textbooks is decreased. The highest number of safety education contents unit is 'Self-management of youth' which includes three parts of safety education. In the case of a unit for emphasizing practice, experience and practical exercise such as 'Life of youth' and 'Practice of eco-living', safety education content in the area of 'life safety' are mostly contained. Safety accidents related to the most student experienced, Household accidents (1.4%) and experiment or practice accidents (0.3%) are presented in a low figure. The contents of universal housing and school violence are duplicated on first and second volume of text. The most presented safety education content in the 12 types of textbooks are proper sexual attitude, dietary problems, family conflict and food choice. The least common contents are dangerous drugs, family welfare, internet addiction and industrial accident compensation insurance. As this study is to analyze 12 textbooks developed in 2009 revision curriculum, it is necessary to compare it with the textbook written by the revised curriculum in 2015 and to clarify the contents system of safety education and to avoid duplication of contents. In addition, it is necessary to develop and distribute a safety education program that can support textbooks.

• Journal of Science Education
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• v.32 no.1
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• pp.33-46
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• 2008

The purpose of this study was to know whether or not any wrongful description or simple errors were in photosynthesis unit of Biology II textbook under 7th national curriculum and if so, to know whether or not high school teachers recognized and corrected properly the mistakes. The mistakes in photosynthesis unit of text books were determined by the comparison with several reference books and through examination by three plant physiologists in 8 different Biology II textbooks. After the mistakes were analysed, the survey using contents of textbook containing the mistakes was conducted on high school teachers teaching Biology II. As a result, 48 mistakes were determined in 13 subjects. As many as four mistakes were found even in one subject in a certain textbook and a same mistake was found repeatedly in several textbooks. The survey result showed that the teachers who pointed exactly the mistakes out corrected properly, however, the percentage of these ones out of 35 teachers replied to survey was less than 50%. The ratios of correction out of total number of responses were high in question #6 (43%), #4-3 (40%), and #1-2 (32%) which were containing a simple mistake in graph, a wrong word and a wrong picture, respectively. But, no one pointed out and made correction in question #5-1 and #5-2 which were containing Z scheme of light reaction without the legend of vertical axis that should be explained as electron energy or standard reduction potential. The result indicates the possibility that the mistakes in photosynthesis unit of Biology II textbook can be corrected and teached properly by teachers may be low. In order to reduce the possibility that students may have misconceptions about photosynthesis, the list of print's errors should be provided to the teachers and/or the training program and/or workshop for in-service high school biology teachers was recommended.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.7-32
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• 2013

The goal of the present study is to identify the topic trend in the field of library and information science in Korea. To this end, we collected titles and s of the papers published in four major journals such as Journal of the Korean Society for information Management, Journal of the Korean Society for Library and Information Science, Journal of Korean Library and Information Science Society, and Journal of the Korean BIBLIA Society for library and Information Science during 1970 and 2012. After that, we applied the well-received topic modeling technique, Latent Dirichlet Allocation(LDA), to the collected data sets. The research findings of the study are as follows: 1) Comparison of the extracted topics by LDA with the subject headings of library and information science shows that there are several distinct sub-research domains strongly tied with the field. Those include library and society in the domain of "introduction to library and information science," professionalism, library and information policy in the domain of "library system," library evaluation in the domain of "library management," collection development and management, information service in the domain of "library service," services by library type, user training/information literacy, service evaluation, classification/cataloging/meta-data in the domain of "document organization," bibliometrics/digital libraries/user study/internet/expert system/information retrieval/information system in the domain of "information science," antique documents in the domain of "bibliography," books/publications in the domain of "publication," and archival study. The results indicate that among these sub-domains, information science and library services are two most focused domains. Second, we observe that there is the growing trend in the research topics such as service and evaluation by library type, internet, and meta-data, but the research topics such as book, classification, and cataloging reveal the declining trend. Third, analysis by journal show that in Journal of the Korean Society for information Management, information science related topics appear more frequently than library science related topics whereas library science related topics are more popular in the other three journals studied in this paper.

• 대한공업교육학회지
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• v.37 no.1
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• pp.145-164
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• 2012

The purpose of this study is to develope the teaching materials of career education for the 'Information and Communication Technology and Our Life' unit in the technology education. As preparation phase, in order to choose the suitable contents for career education, we analyzed the technology education curriculum and 'Information and Communication Technology and our Life' unit of technology and home economics. And then we compared and analyzed the existing related researches. After content analysis of the teaching materials for career education, we mapped the contents into career education area. In the 'Design' step of teaching, we extracted the unit design components after analyzing 'Development in Information and Communication Technology' unit of eleven text books used in 2007 revised curriculum In the 'Introduction', 'Activity', 'Arrangement' steps of teaching, by applying the SHIP model, one of career education program model, we develop the teaching materials. Then, we get expert evaluation using questionnaire and improve the suitability of the teaching materials. The results are as followings: First, our teaching materials reflect the development history of information and communication technology well, show the features of career education, and are suitable to middle school students as the teaching materials. Second, our teaching materials can help students to face various jobs related with the development of Information and communication technology, to have more interests and exploring opportunities about 'Information and Communication Technology' subject. Third, our teaching materials can help teachers to use it for the career education of 'Information and Communication Technology and our Life' unit of 2007 revised curriculum in the class time. Our teaching materials can also be used in the extra activity related to career education and the Creative Experience Activities. Furthermore, since 2009 revised curriculum includes the career education unit in the 'Information and Communication Technology' subject, our teaching materials can be used partially as the teaching materials in the future.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.177-189
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• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.