• Journal of Internet Computing and Services
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• 제15권4호
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• pp.21-31
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• 2014

As the protein drug industry is growing, protein informations are indispensable for the protein drug development. NCBI and PDB in the U.S., the EMBL in Europe and the DDBJ in Japan are the representative centers for bio information and each center provides specific data for protein information. To obtain specific protein information, users are to be collect them from the service sites of each center and then combine or analyze for their purpose. To facilitate the accessibility to bio data, various R&D activities are running for development of diverse web services relevant to bio data in major data centers or small-scale projects. With the recognition of protein information as pivotal for the protein drug development, DrugBank in Canada, GDSC in the U.S. start to provide integrated informations between drugs and proteins. However, those service does not meet users' demands due to lack of diversity. In Korea, infra structures for bioinformatics are limited and the current services for protein drug information are providing only basic information of the drug including distribution data. This is a pilot study to construct a specialized service for protein drug information in Korean style breaking through the limitations of current services. This study proposed new fields for protein characterization information which had not been provided by current services and evaluated their effectiveness and usability by comparing them to the existing fields with expert survey. As a result, the newly proposed fields for protein characterization have been proven to be useful data fields for the service of protein drug information.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제42권6호
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• pp.1-10
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• 2005

This paper describes the implementation of HTML converter for wireless internet access in wireless application protocol environment. The implemented HTML converter consists of the contents conversion module, the conversion rule set, the WML file generation module, and the frame contents reformatting module. Plain text contents are converted to WML contents through one by one mapping, referring to the converting rule set in the contents converting module. For frame contents, the first frameset sources are parsed and the request messages are reconstructed with all the file names, reconnecting to web server as much as the number of files to receive each documents and append to the first document. Finally, after the process of reformatting in the frame contents reformatting module, frame contents are converted to WML's table contents. For image map contents, the image map related tags are parsed and the names of html documents which are linked to any sites are extracted to be replaced with WML contents data and linked to those contents. The proposed conversion method for frame contents provides a better interface for the users convenience and interactions compared to the existing converters. Conversion of image maps in our converter is one of the features not currently supported by other converters.

• Journal of KIISE:Computing Practices and Letters
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• 제8권1호
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• pp.71-81
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• 2002

The lack of specialties of the existing commercial web search systems stems from the fact that they have no capabilities to extract and gather the meaningful information from each information domain they cover. We are sure, however, that the necessity for the information integration system, not just search system, will be likely to become larger in the future. In this paper, we propose a design and implementation of an information integration system called TIC(target information collector). TIC is able to extract meaningful information from a specific information area in the internet and integrate them for the commercial service. We also show the evaluation results of our implementation. For the experiments we applied our TIC to the international procurement information area. The international procurement information is publicly and freely announced by each government to the world. To automatically extract common properties from the related source sites, we adopt information pointing technique using inter-HTML tag pattern parsing. And through the information integration framework design, we can easily implement a site-specific information integration engine. By running our TIC for about 8 months, we find out it can remove considerable amount of the duplicated information, and as a result, we can obtain high quality international procurement information. The main contribution of this paper is to present a framework design and it's implementation for extracting the information of a specific area and then integrating them into a meaningful one.

• Journal of Korea Entertainment Industry Association
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• 제13권6호
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• pp.53-67
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• 2019

This study is expected to be of significance in that it attempted to examine the personal information protection awareness of college students and the state of their personal information protection as prospective information processors and private information owners to boost their will to put private information protection in practice. As a result of making an analysis, the most common average time that the students spent in doing every online activity on weekdays was fewer than two or three hours, and the most dominant activities that they did over the Internet were for entertainment or hobbies. As for awareness of the nature of the Internet, they looked upon it as a quite open public space. Regarding the state of private information protection, they thought that changing passwords on a regular basis would be beneficial to personal information protection, and many thought that it's needed to withdraw from or shut down web sites that weren't used for a long time. In terms of actual practice, however, they didn't change their e-mail passwords regularly on the grounds that it's a hassle, and even the students who had experience of personal information leakage didn't report it or didn't ask for counsel on the grounds that they didn't want to be bothered as well. The majority of the students weren't cognizant of how to report or seek counsel. In the future, personal information protection should be educated on a continual basis as part of curriculum to raise awareness of it among students and boost their will to practice it with a sense of responsibility in an effort to prevent the occurrence of collateral damages triggered by personal information leakage.

• Journal of Intelligence and Information Systems
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• 제21권4호
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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 Intelligence and Information Systems
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• 제20권3호
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• pp.59-76
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• 2014

The revolution of smart media such as smart phone, smart TV and tablets has brought easiness for people to get contents and related information anywhere and anytime. The characteristics of the smart media have changed user behavior for watching the contents from passive attitude into active one. Video is a kind of multimedia resources and widely used to provide information effectively. People not only watch video contents, but also search for related information to specific objects appeared in the contents. However, people have to use extra views or devices to find the information because the existing video contents provide no information through the contents. Therefore, the interaction between user and media is becoming a major concern. The demand for direct interaction and instant information is much increasing. Digital media environment is no longer expected to serve as a one-way information service, which requires user to search manually on the internet finding information they need. To solve the current inconvenience, an interactive service is needed to provide the information exchange function between people and video contents, or between people themselves. Recently, many researchers have recognized the importance of the requirements for interactive services, but only few services provide interactive video within restricted functionality. Only cooking domain is chosen for an interactive cooking video query service in this research. Cooking is receiving lots of people attention continuously. By using smart media devices, user can easily watch a cooking video. One-way information nature of cooking video does not allow to interactively getting more information about the certain contents, although due to the characteristics of videos, cooking videos provide various information such as cooking scenes and explanation for each recipe step. Cooking video indeed attracts academic researches to study and solve several problems related to cooking. However, just few studies focused on interactive services in cooking video and they still not sufficient to provide the interaction with users. In this paper, an interactive cooking video query service system with linked data to provide the interaction functionalities to users. A linked recipe schema is used to handle the linked data. The linked data approach is applied to construct queries in systematic manner when user interacts with cooking videos. We add some classes, data properties, and relations to the linked recipe schema because the current version of the schema is not enough to serve user interaction. A web crawler extracts recipe information from allrecipes.com. All extracted recipe information is transformed into ontology instances by using developed instance generator. To provide a query function, hundreds of questions in cooking video web sites such as BBC food, Foodista, Fine cooking are investigated and analyzed. After the analysis of the investigated questions, we summary the questions into four categories by question generalization. For the question generalization, the questions are clustered in eleven questions. The proposed system provides an environment associating UI (User Interface) and UX (User Experience) that allow user to watch cooking videos while obtaining the necessary additional information using extra information layer. User can use the proposed interactive cooking video system at both PC and mobile environments because responsive web design is applied for the proposed system. In addition, the proposed system enables the interaction between user and video in various smart media devices by employing linked data to provide information matching with the current context. Two methods are used to evaluate the proposed system. First, through a questionnaire-based method, computer system usability is measured by comparing the proposed system with the existing web site. Second, the answer accuracy for user interaction is measured to inspect to-be-offered information. The experimental results show that the proposed system receives a favorable evaluation and provides accurate answers for user interaction.

• Journal of Korean Home Economics Education Association
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• 제19권2호
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• pp.1-12
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• 2007

This study analyzed the recognition and utilization regarding teacher's guidebook for middle school technology-home economics class in the 7th Educational Curriculum. The data were collected via e-mail to teachers teaching home economics in middle schools. These e-mail addresses were acquired from middle school web pages registered on the Educational Board. The 355 data were analyzed using the SPSS program. The results were as follows: First, teachers recognized highly the necessity of teacher's guidebook. However, as the actual guidebook was not adequately helpful, the overall degree of satisfaction was relatively low. Teachers utilizing guidebook had more positive recognition on teacher's guidebook than teachers who did not. And teachers majored in technology education thought teacher's guidebook more helpful compared with teachers majored in home economics education. Second, teachers referenced teacher's guidebook mostly for field practice guidance. Third, teachers who did not utilize teacher's guidebook used other reference materials such as Internet Web sites and audiovisual materials. They were most commonly used for the reason that the contents were ample and easy to access. Fourth, the followings were suggested to improve teacher's guidebook. The provision of learning contents that can be practically used in class, the various samples of teaching-learning method, the specified methods of planning and criteria for performance assessment, the adequate supplementations regarding textbook contents, and the improvement of the outward layout format of the guidebook.

• Journal of Intelligence and Information Systems
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• 제20권2호
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Korean Journal of Environmental Agriculture
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• 제37권4호
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• pp.251-259
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• 2018

BACKGROUND: Various culture media have been used for hydroponic cultures of horticultural plants under the smart greenhouses with natural and artificial light types. Management of the culture medium for the control of medium amounts and/or necessary components absorbed by plants during the cultivation period is performed with ICT (Information and Communication Technology) and/or IoT (Internet of Things) in a smart farm system. This study was conducted to develop the cloud-based data analysis system for effective management of culture medium applying to hydroponic culture and plant growth in smart greenhouses. METHODS AND RESULTS: Conventional inorganic Yamazaki and organic media derived from agricultural byproducts such as a immature fruit, leaf, or stem were used for hydroponic culture media. Component changes of the solutions according to the growth stage were monitored and plant growth was observed. Red and green lettuce seedlings (Lactuca sativa L.) which developed 2~3 true leaves were considered as plant materials. The seedlings were hydroponically grown in the smart greenhouse with fluorescent and light-emitting diodes (LEDs) lights of $150{\mu}mol/m^2/s$ light intensity for 35 days. Growth data of the seedlings were classified and stored to develop the relational database in the virtual machine which was generated from an open stack cloud system on the base of growth parameter. Relation of the plant growth and nutrient absorption pattern of 9 inorganic components inside the media during the cultivation period was investigated. The stored data associated with component changes and growth parameters were visualized on the web through the web framework and Node JS. CONCLUSION: Time-series changes of inorganic components in the culture media were observed. The increases of the unfolded leaves or fresh weight of the seedlings were mainly dependent on the macroelements such as a $NO_3-N$, and affected by the different inorganic and organic media. Though the data analysis system was developed, actual measurement data were offered by using the user smart device, and analysis and comparison of the data were visualized graphically in time series based on the cloud database. Agricultural management in data visualization and/or plant growth can be implemented by the data analysis system under whole agricultural sites regardless of various culture environmental changes.

• Journal of the Korea Convergence Society
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• 제8권2호
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• pp.91-97
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• 2017

The purpose of the study was to investigate the fire fighter image through disaster movies in Korea and other countries. From September 1 to 7, 2016, the movie search methods were carried out using movie title and key words via Wikipedia and various internet web sites from 1903 to 2016. The results included that the fire fighters had been considered as the precious person of volunteer activity regarding fire suppression, investigators, and self-sacrifice. Through the convergence and integration review of the disaster movie, this research suggested that the national based establishment of the welfare and safety system for the posttraumatic stress disorder(PTSD) and critical incident stress management(CISM) education program. This study will provide the basic data for the development of welfare and safety management for the fire fighters and let the people know the sacrifice of the fire fighters including the motto, "First in and the last out".