• Journal of Digital Convergence
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• v.14 no.8
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• pp.57-67
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• 2016

As the Internet is becoming more socialized, Korean government, publishing a slogan, Government 3.0, has recently began to find a way to deliver its administration services to the public in more personalized manner. Policy directions to implement this advanced idea, are however still at large, primarily because of the vague nature of 'personalized'. This study, therefore, explores the possibility of getting public administrative services closer to personalization. To achieve this objective, this study attempts to develop a integrative framework of classifying the administration services to the public, based on two dimensions - the degree of citizen-oriented and the degree of government-driven, both of which are perhaps key determinants of personaliztion of services. For each quadrant of the framework, key features, characteristics, and conditions to be met are explained and followed by exemplary cases and policy implications.

• MALSORI
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• no.43
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• pp.113-125
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• 2002

As there are needs to search the Web information via wire or wireless telephones, VoiceXML forum was established to develop and promote the Voice eXtensible Markup Language (VoiceXML). VoiceXML simplifies the creation of personalized interactive voice response services on the Web, and allows voice and phone access to information on Web sites, call center databases. Also, it can utilize the Web-based technologies, such as CGI(Common Gateway Interface) scripts. In this paper, we have developed the voice portal service platform based on VoiceXML called TeleGateway. It enables integration of voice services with data services using the Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) engines. Also, we have showed the various services on voice portal services.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.21-26
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• 2018

Recently, data analysis technology through artificial intelligence is attracting major attention in various industrial fields. In addition, with the increase in personal income, nowadays, the importance of heterogeneous leisure life is becoming more prominent. However, there is a problem that the tourism industry is not out of the traditional service framework. For the ultimate development of the tourism industry, it is time to provide more scientific and systematic tourism services. In this paper, various data analysis techniques in the field of computer science are applied to the field of tourism to realize next generation tourism services. To this end, the scope of this study is limited to the aviation service, and a natural ecosystem of the aviation industry for future-oriented services of aviation tourism that can improve the efficiency of aviation service gradually is established. The proposed method effectively solves the problems of traditional aviation services through data analysis techniques with artificial intelligence techniques in computer science. We expect that it will enhance the customized satisfaction of customers through personalized service and foster loyal customers in aviation companies through the method proposed.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.173-177
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• 2009

With the advent of light-weight daily physiological signal monitoring sensors, intelligent inference and analysis method for physiological signal monitoring application, commercialized products and services are released. However, practical constraints still remain for daily physiological signal monitoring. Most devices provide rough health check function and analyze with randomly sampled measurements. In this work, we propose the probabilistic modeling of physiological signal analysis. This model represent the relationship between previous user measurement (history), other group`s type, model and current observation. From the experiment, we found that the personalized analysis with long term regular data shows reliable result and reduces the analyzing errors. In addition, participants agree that the personalized analysis shows reliable and adaptive information than other standard analysis method.

• 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 Genetic Medicine
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• v.5 no.2
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• pp.89-93
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• 2008

"Personalized medicine," the goal of which is to provide better clinical care by applying patient's own genomic information to their health care is a global challenge for the $21^{st}$ century "genomic era." This is especially true in Korea, where provisions for clinical genetic services are inadequate for the existing demand, let alone future demands. Genomics-based knowledge and tools make it possible to approach each patient as a unique biological individual, which has led to a paradigm-shift in medical practice, giving it more of a predictive focus as compared with current treatment oriented approach. With recent advancements in genomics, many genetic tests, such as susceptibility genetic tests, have been developed for both rare single gene diseases and more common multifactorial diseases. Indeed, genetic tests for presymtomatic individuals and genetic tests for drug response have become widely available, and personalized medicine will face the challenge of assisting patients who use such tests to make appropriate and wise use of genetic risk assessment. A major challenge of genomic medicine lies in understanding and communicating disease risk in order to facilitate and support patients and their families in making informed decisions. Establishment of a health care system with provisions for genetic counseling as an integral part of health care service, in addition to genomic literacy of health care providers, is vital to meet this growing challenge. Realization of the promise of personalized medicine in the era of genomics for improvement of health care is dependent on further development of next generation sequencing technology and affordable sequencing test costs. Also necessary will be policy development concerning the ethical, legal and social issues of genomic medicine and an educated and ready medical community with clinical practice guidelines for genetic counseling and genetic testing.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1740-1748
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• 2014

In this paper, we propose an RBAC based personalized health care service platform in order to provide smart management of personal health record using smart devices. It helps to guide healthful service and provide useful information according to one's individual health record. Personalized health care services platform supports a healthy lifestyle by measuring personal health information in a hospital clinical, imaging, and drug data, as well as that can be obtained from smart devices. Everyone can enter his health related data in everyday life such as food, sleeping time, mood, movement and exercise so that one can manage his personal health information of modern smart features. In addition, if necessary, personal health information can be provided to the hospital information system and staff with the consent of the individual. It can be contributed to simplify the complex process for remote medical. The proposed platform, which applies role based access control model to protect security and privacy, supports a smart health care services for users by providing personalized health care services through the smart applications.