• Archives of design research
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• v.16 no.2
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• pp.57-66
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• 2003

In order to develop color image, color simulation based on data processing techniques has been developed and applied to data interpretation tools or product design supporting systems. It has been a commonmethod to use image key words to search for data and provide color coordination samples that determine computer combination in computerized support systems until recently. However, this method does not reflect system designers and users taste or preference on making final choices of color coordination samples because the database was designed based on an assumption of standardized group that was established database from large scaled image evaluation research. In this study, we suggest a color coordination simulator that supports designer's final decision-making procedure on sample groups through the simulation of various color combination. The simulator allows communications with the system to explore a designer's color combination taste and preference, and provides a user for an efficient environment to judge the optimum result. The color coordination simulator was designed based upon Dual mapping model derived from a designer's thought process, and four steps of operations longrightarrowdefining color concept longrightarrowmaking color sample groupslongrightarrow simulation-determining ranking among final combination samples - will be assisting color design process.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.119-128
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• 2013

Most internet users utilize internet portal search engines, such as Naver, Daum and Google nowadays. But since the results of internet portal search engines are based on universal criteria (e.g. search frequency by region or country), they do not consider personal interests. Namely, current search engines do not provide exact search results for homonym or polysemy because they try to serve universal users. In order to solve this problem, this research determines keyword importance and weight value for each individual search characteristics by collecting and analyzing customized keyword at external database. The customized keyword weight values are integrated with search engine results (e.g. PageRank), and the search ranks are rearranged. Using 50 web pages of Goolge search results for experiment and 6 web pages for customized keyword collection, the new customized search results are proved to be 90% match. Our personalization approach is not the way that users enter preference directly, but the way that system automatically collects and analyzes personal information and then reflects them for customized search results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.209-221
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• 1999

Several approaches to anlayzing real-time schedulability have been presented, but since these used a fixed priority scheduling scheme and/or traverse all possible state spaces, there take place exponential time and space complexity of these methods. Therefore it is necessary to reduce the state space and detect schedulability at earlier time. This paper proposes and implements an advanced schedulability analysis algorithm to determine that is satisfied a given deadlines for real-time processes. These use a minimum execution time of process, periodic, deadline, and a synchronization time of processes to detect schedulability at earlier time and dynamic scheduling scheme to reduce state space using the transition rules of process algebra. From a result of implementation, we demonstrated the effective performance to determine schedulability analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.502-503
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• 2019

In the existing system that recommends through review data analysis, it does not reflect personal preference details such as user's characteristics or product purchase tastes, in this paper, we propose a system that provides customized recommendation information to various users by selecting the criterion that the user thinks most importantly when searching for the product and purchasing the product, and analyzing it. This is because the user's personal preference is reflected by arranging the product list based on the criterion that the user occupies the largest portion of the product purchase, so that it is more efficient than the recommendation through the recommendation system.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.32-39
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• 2009

Semantically-operated services, which is different from Web services or semantic Web services with semantic markup, can be defined as the services providing search function or reasoning function using ontologies. It performs a pre-defined task by exploiting URI, ontology classes, and ontology properties. This study introduces a method for pipelining semantically-operated services based on a semantic broker which refers to ontologies and service description stored in a service manager and invokes by user constraints. The constraints consist of input instances, an output class, a visualization type, service names, and properties. This method provides automatically-generated service pipelines including composit services and a simple workflow to the user. The pipelines provided by the semantic broker can be executed in a fully-automatic manner to find a set of meaningful semantic pipelines. After all, this study would epochally contribute to develop a portal service by ways of supporting human service planners who want to find specific composit services pipelined from distributed semantically-operated services.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.303-314
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• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.543-551
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• 2015

As the use of internet and mobile devices became generalized, users utilizing search and recommendation in order to find the information they want in the midst of various websites have become common. In order to recommend more appropriate item for users, this paper proposes a recommendation technique that reflects the users' preference change following the flow of time by applying users' activity and time information. The proposed technique, after classifying the data in categories including the tag information that is considered at the time of choosing the items, only uses the data that users' preference change following the flow of time is reflected. For the users who prefer the corresponding category, the item that is extracted by applying tag information to collaboration filtering technique is recommended and for general users, items are recommended based on the ranking calculated by using the tag information. The proposed technique was experimented by using hetrec2011-movielens-2k data set. The experiment result indicated that the proposed technique has been more enhanced the accuracy, appropriacy, compared to item-based, user-based method.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.499-503
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• 2024

Broadcasting programs are provided to various media such as Internet replay, OTT, and IPTV services as well as self-broadcasting. In this case, it is very important to provide keywords for search that represent the characteristics of the content well. Broadcasters mainly use the method of manually entering key keywords in the production process and the archive process. This method is insufficient in terms of quantity to secure core metadata, and also reveals limitations in recommending and using content in other media services. This study supports securing a large number of metadata by utilizing closed caption data pre-archived through the DTV closed captioning server developed in EBS. First, core metadata was automatically extracted by applying Google's natural language AI technology. The next step is to propose a method of finding core metadata by reflecting priorities and content characteristics as core research contents. As a technology to obtain differentiated metadata weights, the importance was classified by applying the TF-IDF calculation method. Successful weight data were obtained as a result of the experiment. The string metadata obtained by this study, when combined with future string similarity measurement studies, becomes the basis for securing sophisticated content recommendation metadata from content services provided to other media.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.17-44
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• 2022

The purpose of this study was to present a plan on the effect of non-face-to-face services on library anxiety facilities by analyzing the library anxiety factors of university library users. To this end, we look at the cases of university library user service response activities in response to the COVID-19 crisis and select 40 schools with the highest number of library visitors per student from among domestic four-year university libraries with 5,000 or more and less than 10,000 students. Methods of information service and program cases were analyzed, and K-LAS was reconstructed and surveyed for current students using the K university library, and frequency analysis, descriptive statistical analysis, exploratory factor analysis, and reliability analysis, correlation analysis, and multiple regression analysis were applied to analyze the library anxiety factors of users. Identify the relationship between 5 library anxiety factors and non-face-to-face service activation factors, such as physical/environmental factors of the library, data search selection factors, digital information system factors, librarian (staff) factors, and psychological/emotional factors, and activate non-face-to-face services. The influence of these factors on library anxiety factors was examined, and as a result, it was found that non-face-to-face service activation factors had the greatest influence on library digital information system anxiety factors. Based on the analysis results, it was attempted to derive a plan to relieve users' library anxiety by activating non-face-to-face services.