• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.172-182
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• 2008

Application Contents of based on a workflow process unit in grid system is a practical work to solve the problem. To construct cooperation environment is very important because the contents are deployed and executed. And the most of cooperation is executed by workflow. Globus toolkit is the middleware for cooperation process in grid environment. However the middleware only provides basic services for constructing grid, not workflow that can provides cooperation, job scheduling, application contents management. Also Globus toolkit is suitable for huge gird community but small size pc based grid community. Therefore, this paper proposes the efficient application contents deployment system for small sizes cooperation. This system supports efficient cooperation environment with Application contents deployment and resource management provided in grid community. Also it presents information and association relation among application contents with association dictionary among application contents based on workflow process unit, and utilizes this as information for application contents deployment.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.9-18
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• 2010

As digital contents become vast in quantity, it takes long time for users to search the digital contents they want, which is a problem that has arisen. Therefore, it is required to have the technology that analyzes vast digital contents and extracts the appropriate contents for users in order to provide them with contents they want. For a fast searching of digital contents suitable for users, it is necessary to have the technology of filtering for digital contents. In this paper, we propose a method of filtering digital contents suitable for individual users. The method suggested in this paper is to analyze case-based information in digital contents and provide the digital contents suitable for individual users. The case for using digital contents is used for analysis of users' preference. Various simulations were conducted to confirm the effectiveness of the proposed method.

• The Journal of Korean Association of Computer Education
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• v.6 no.3
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• pp.75-85
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• 2003

This study develops the System(MetaGene) to create meta-data for learning object based on SCORM including meta-data of Assets. SCO, Contents Aggregation and metadata of Contents Package. API function cocle is embeded in Learning Object for interfacing API adopter in LMS to support SCORM and for tracking on learning process based on data models. Also, the learning objects are packaged the PIF(Packaged Interchange File) to transmit with LMS. MetaGene is verified by $SCORM^{(TM)}$ Conformance TestSuite for meta-data of learning objects, manifest file of Contents Packaging.

• Management Science and Financial Engineering
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• v.16 no.2
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• pp.29-38
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• 2010

As the Internet is more embedded in people's lives, Internet users draw on new Internet applications to express themselves through "user-created content (UCC)." In addition, there is a noticeable shift from text-centered contents mainly posted on bulletin boards to multimedia contents such as images and videos on UCC web sites. The changes require different way of recommendations comparing to traditional products or contents recommendation on the Internet. This paper aims to design UCC recommendation methods with user behavior data and contents metadata such as tags and titles, and compare performances of the suggested methods. Real web logs data of a major Korean video UCC site was used to empirical experiments. The results of the experiments show that collaborative filtering technique based on similarity of UCC customers' preferences performs better than other content-based recommendation methods based on tag information and content metadata.

• Journal of Digital Convergence
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• v.6 no.1
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• pp.35-41
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• 2008

The digital economic environment of next generation, which digital high-technology industry appears to be the economic center of the high degree of industry structure, is expected to be developed as the existing traditional industry is merged with high tech digital one. The developing system of contents policy for digital industry means the policy and vision, and strategic structure which get the mechanism of contents industry structure to work. The promotion organization of digital contents policy is requested to secure the framework of digital contents industry based on cluster, the infra framework of digital infra culture, the infra framework of industry-academic cooperation, and the overall digital contents based on motive policy for the vitality of the youth. The application of digital contents policy may lead to establish the framework of the growth for the every unit of industry with the cluster oriented system.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.27-40
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• 2023

With the increase in the spread of smart devices and the impact of COVID-19, the consumption of media contents through smart devices has significantly increased. Along with this trend, the amount of media contents viewed through OTT platforms is increasing, that makes contents recommendations on these platforms more important. Previous contents-based recommendation researches have mostly utilized metadata that describes the characteristics of the contents, with a shortage of researches that utilize the contents' own descriptive metadata. In this paper, various text data including titles and synopses that describe the contents were used to recommend similar contents. KLUE-RoBERTa-large, a Korean language model with excellent performance, was used to train the model on the text data. A dataset of over 20,000 contents metadata including titles, synopses, composite genres, directors, actors, and hash tags information was used as training data. To enter the various text features into the language model, the features were concatenated using special tokens that indicate each feature. The test set was designed to promote the relative and objective nature of the model's similarity classification ability by using the three contents comparison method and applying multiple inspections to label the test set. Genres classification and hash tag classification prediction tasks were used to fine-tune the embeddings for the contents meta text data. As a result, the hash tag classification model showed an accuracy of over 90% based on the similarity test set, which was more than 9% better than the baseline language model. Through hash tag classification training, it was found that the language model's ability to classify similar contents was improved, which demonstrated the value of using a language model for the contents-based filtering.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.438-447
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• 2011

geoContents have been closely related with personal life since the Google Earth and Street View by Google and the Road View by Daum were introduced. So, Location-based content, which is referred to geoContents, involving geometric spacial information and location-based image information is a sharp rise in demand. A mobile mapping system used in the area of map upgrade and road facility management has been having difficulties in satisfying the demand in the cost and time for obtaining these kinds of contents. This paper addresses geoData acquisition and processing system for producing panoramic images. The system consists of 3 devices: the first device is 3 GPS receivers for acquiring location information which is including position, attitude, orientation, and time. The second is 6 cameras for image information. And the last is to synchronize the both data. The geoData acquired by the proposed system and the method for authoring geoContents which are referred to a panoramic image with position, altitude, and orientation will be used as an effective way for establishing the various location-based content and providing them service area.

• Korean Journal of Community Nutrition
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• v.22 no.2
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• pp.115-126
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• 2017

Objectives: The purpose of the study was to develop communication strategies for effective nutrition education targeting pregnant women and to create nutrition education contents. Methods: The format and the contents of online resources on nutrition information for pregnant women provided by reliable institutions were analyzed. Possible solutions to overcome barriers of nutrition education as well as communication strategies for effective nutrition education were identified by a brainstorming process. Based on the communication strategies, contents for nutrition education were created. Understandability, level of interest, applicability to daily life, harmony of text and illustration, and overall satisfaction of the contents were evaluated by dietitians and pregnant women. Results: The four communication strategies were developed; (1) to focus on a few important messages, (2) to provide evidence-based information, (3) to create illustrations or infographics with a minimum amount of text, and (4) to provide tips on how to improve the current diet options. Based on these strategies, the contents were focused on three important nutrients for pregnant women, folate, iron, and calcium. The percentages of the recommended nutrient intakes of the three nutrients on selected menu and its improved version by adding a dish or changing a dish into another dish were calculated and provided. Finally, the contents were delivered as illustrations with a minimum amount of text. Overall, dietitians and pregnant women were satisfied with the contents. Conclusions: The contents developed in this study can be used in a pamphlet or a pregnancy diary, or can be shared in social networking services. Further contents on other nutrients and various menu are expected to be developed using these communication strategies.

• ETRI Journal
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• v.39 no.2
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• pp.191-201
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• 2017

This paper proposes an approach using taxonomic relatedness for answer-type recognition and type coercion in a question-answering system. We introduce a question analysis method for a lexical answer type (LAT) and semantic answer type (SAT) and describe the construction of a taxonomy linking them. We also analyze the effectiveness of type coercion based on the taxonomic relatedness of both ATs. Compared with the rule-based approach of IBM's Watson, our LAT detector, which combines rule-based and machine-learning approaches, achieves an 11.04% recall improvement without a sharp decline in precision. Our SAT classifier with a relatedness-based validation method achieves a precision of 73.55%. For type coercion using the taxonomic relatedness between both ATs and answer candidates, we construct an answer-type taxonomy that has a semantic relationship between the two ATs. In this paper, we introduce how to link heterogeneous lexical knowledge bases. We propose three strategies for type coercion based on the relatedness between the two ATs and answer candidates in this taxonomy. Finally, we demonstrate that this combination of individual type coercion creates a synergistic effect.

• Korean Institute of Interior Design Journal
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• v.21 no.6
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• pp.46-53
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• 2012

The purpose of present study is that according to the changing tourism environment, detailed cultural environment will be utilized in the active way as systematized theme-based cultural space, and the increase of small theme-based cultural space will contribute to active participation of customers and local development with various programs. TCS was classified to theme-based cultural space contents E5(Education, Entertainment, Experience, Emotion and Economy) in focus of contents in which software is regarded more importantly than hardware, and was analyzed as contents of ten key tourism trend of the future. The present study indicate that experience centered tourism environment stood out in theme-based cultural space, and new era of cultural tourism to which storytelling in focus of emotion is applied will be coming.