• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.631-639
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• 2014

Since digital broadcasting service has been begun, user's requirements have been increased for personalized broadcasting system that users can watch the part of programs which they want to watch in anytime. In personalized broadcasting system, metadata is important for searching program information based on user's input data. In this paper, an object-oriented media service metadata management module is implemented. Metadata used in this system is described by extending TV-Anytime specifications which is the International standard for personalized media service. For this, extended segments information is provided including object information which do not existing in previous personalized broadcasting standard. This system can provide better satisfaction to users by using object segmentation information.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.528-543
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• 2008

Internet Protocol Television (IPTV) provides an interactive and personalized service for realizing integrated broadcasting and telecommunication services. Set-top box (SIB) connected to TV is an essential component required for IPTV and has a unique hardware identifier used in identification and authentication. It means that subscriber authentication based on box-level identification is inconsistent with IPTV's main intention of providing personalized services. The proposed solution is to provide an opportunity to use the flexible user-centric authentication mechanism through Java Card applets in IPTV application server and 3G networks. This paper suggests personalized services by moving the user's private data and authentication management beyond the STB to a truly personalized device, the ubiquitous mobile phone. In addition, this paper presents effectiveness and security analysis for verifying the proposal.

• Management & Information Systems Review
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• v.38 no.1
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• pp.23-41
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• 2019

Smart Factory is different from existing factory automation in that it aims to produce personalized products with minimum time and cost through ICT. However, previous researches, not from consumers but from product suppliers, have focused on technology trends and technology application methods. In order for Smart Factory to be successful, it must go beyond supplier-focus to meet the needs of consumers. In this study, we surveyed the purchase intention of the personalized product manufactured by smart factory. Influencing factors of purchase intention were drawn as consumers' need for uniqueness, innovativeness, need for touch, and privacy concern, based on previous research. As results of data analysis, it was confirmed that respondents were willing to purchase personalized products, and that consumers' need for uniqueness, innovativeness, and need for touch had a significant impact on purchase intention of personalized products. Our findings can be summarized as follows. First, Consumers' need for uniqueness was found to have positive effects(${\beta}=0.168$) on purchase intention of personalized products. The desire to differentiate themselves from others will be reflected in their personalized products. Therefore, consumers with a higher desire for uniqueness tend to be more willing to purchase personalized products. Second, consumer innovativeness was found to have positive effects(${\beta}=0.233$) on purchase intention of personalized products. Personalized shoes suggested in this study is a new type of personalized product that is manufactured by the latest information and communication technologies such as multi-function robots and 3D printing. Therefore, consumers seeking innovative new experiences are more willing to purchase personalized products. Third, need for touch was found to have positive effects(${\beta}=0.299$) on purchase intention of personalized products. In a smart factory environment, prosuming participation is given to consumers. If consumers participate in the product development process and reflect their requirements on the product, they are expected to increase their purchase intention by virtually satisfying the need for touch. Fourth, privacy concern was found to have no significantly related to purchase intention of personalized products. This is interpreted as a willingness to tolerate the risk of exposing personal information such as home address, telephone number, body size, and preference for consumers who feel highly useful in personalized products.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.453-454
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• 2017

The travellers using social media leave their location history in the form of trajectories. These trajectories can be bridged for acquiring information, required for future recommendation for the future travelers, who are new to that location, providing all sort of information. In this paper, we propose a personalized travel path recommendation scheme based on social life log. By taking advantage of two kinds of social media such as travelogue and community contributed photos, the proposed scheme can not only be personalized to user's travel interest but also be able to recommend a travel path rather than individual Points of Interest (POIs). It also maps both user's and routes' textual descriptions to the topical package space to get user topical package model and route topical package model (i.e., topical interest, cost, time and season).

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.707-716
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• 2004

Recently, many areas of application such as statistics and industrial engineering are interested in the effective education of databases. In this article we design and implement a database learning system based on learner management techniques. The system supports a personalized/ team-centered learning environment, monitoring the learning attitude of learners, and a method for the assessment.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.37-45
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• 2015

With advancement in information technologies and a better mobile environment, the paradigm of service is shifting again from web portals to networked-applications based on individual application programs. Furthermore, as more investment is being made in R&D, the efforts to enhance R&D productivity are becoming important. In this paper, we designed a personalized service model for developing a tool to assist researchers in their R&D activities. To do this, we first compared services and tools in terms of information activities of researchers in R&D. In addition, we also analyzed changes of information environment such as open expansion of information and data, enhancement of personal information protection, popularization of social networking service, very big contents, advances in web platform technology in terms of personalization, and defined some directions of developing a personalized service. Subsequently we designed a personalized service model of research support tool in the views of functions, contents, operation, and defined personalized design goals and principles for implementing it as standard, participation, and open.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.19-28
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• 2021

Nowadays, interest in health care is increasing due to Coronavirus (COVID-19), and a lot of people are doing home training as there are more difficulties in using fitness centers and public facilities that are used together. In this paper, we propose a personalized exercise recommendation algorithm using personalized propensity information to provide more accurate and meaningful exercise recommendation to home training users. Thus, we classify the data according to the criteria for obesity with a k-nearest neighbor algorithm using personal information that can represent individuals, such as eating habits information and physical conditions. Furthermore, we differentiate the exercise dataset by the level of exercise activities. Based on the neighborhood information of each dataset, we provide personalized exercise recommendations to users through a dimensionality reduction algorithm (SVD) among model-based collaborative filtering methods. Therefore, we can solve the problem of data sparsity and scalability of memory-based collaborative filtering recommendation techniques and we verify the accuracy and performance of the proposed algorithms.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.45-57
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• 2005

In order to provide personalized knowledge recommendation services, most web portals for organizational knowledge management use category or keyword information that portal users explicitly express interests in. However, it is usually difficult to collect correct preference data for all users with this approach, and, moreover, users' preferences may easily change over time, which results In outdated user profiles and impaired recommendation qualify. In order to address this problem, this paper suggests knowledge recommendation methods for portals using user profiles that are automatically constructed from users' activities such as posting or uploading of articles and documents. The result of our experiment shows that the Proposed method can provide equivalent performance with the manual category or keyword selection method.

• KSCI Review
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• v.14 no.2
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• pp.135-139
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• 2006

There have been many suggestions of ontology-based semantic web service systems and recommendation systems, but there has been no attempt to study educational consultation. Thus this study set out to tackle the problem and design specialized service to reflect individuals' interest, aptitude, hobbies, and grades based on the semantic web technology so that they could search the related information easily by managing personal profiles and identifying the meanings between information. It also aimed to suggest a convenient information service system of personalized educational consultation.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.75-87
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• 2024

Purpose: Dietary habits are strongly related to the symptoms of people with irritable bowel syndrome (IBS). Therefore, personalized nutrition management can help reduce symptoms and improve the quality of life of people with IBS. This study assessed the effectiveness of a personalized web-based nutrition management based on the types of food that trigger IBS symptoms. Methods: Sixty Korean adults with IBS according to Rome IV criteria in their 20s and 30s were enrolled in this study. The data from the final 49 patients who completed a three-month personalized nutrition intervention were analyzed. The general information, anthropometry, dietary intake survey, and gut microbiota were examined pre and post-intervention. The gut microbiota analysis included the relative abundance and the Shannon index. The food intake was recorded for two days for personalized nutrition education, followed by three months of personalized nutrition intervention. Statistical analysis was performed using the Wilcoxon signed-rank test in SPSS 26.0, with the significance set to p < 0.05. Results: The relative abundance of the gut microbiota changed after personalized nutrition management, with a significant decrease in the presence of Veillonella (p = 0.048). Furthermore, when the gut microbiota was analyzed according to the type of food that triggers symptoms, the diversity was increased significantly in the high fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) type (p = 0.031) and FODMAPs-containing gluten-type personalized nutrition intervention types (p < 0.001). Conclusions: Gut microbial diversity and gut microbiota distribution changed after using web-based personalized nutrition management. Hence, personalized nutrition management that considers trigger foods may improve IBS symptoms.