• Asia pacific journal of information systems
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• v.9 no.4
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• pp.107-124
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• 1999

This paper describes a personalized advertisement technique as a part of intelligent customer services in Internet shopping malls. Based on customers' initial profile, purchase history, and behaviors in an Internet shopping mall, the technique displays appropriate advertisements on Internet web pages when customers' visit to the shopping mall. Customers preference scores for product groups which are main sources to select advertisements, are stored either a preference table or preference trees. Both of the two storage methods can support selection of advertisements on real time, and the preference tree method can reflect affinity among product groups. The suggested technique selects different advertisements to reflect changes of customers preferences as time goes by. An experiment has been performed to evaluate the effectiveness of the algorithm, which revealed that the algorithm selects more customer-oriented advertisements rather than random selection.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.408-411
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• 2006

Currently, the nano economy threatens the mass economy. This is based on the internet business models. In the nano business models based on internet, the diversely personalized services are needed. Many researches of the personalization on the web have been studied. The web usage mining using click stream data is a tool for personalization model. In this paper, we propose an internet business model using evolutionary support vector machine and web response survey as a web usage mining. After analyzing click stream data for web usage mining, a personalized service model is constructed in our work. Also, using an approach of web response survey, we improve the performance of the customers' satisfaction. From the experimental results, we verify the performance of proposed model using two data sets from KDD Cup 2000 and our web server.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.71-80
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• 2021

Artificial intelligence (AI) will have a huge impact on future education. We look at the role of AI in education and changes in schools. Personalized education is being attempted in limited services, and an interactive tutor service with speech recognition/dialog technology is being developed. In the future, we look forward to fully personalized education for individual students through AI teachers. Teachers are expected to make more effort to teach creative thinking, critical thinking, communication, and collaboration. As the speed of development of AI technology accelerates, we expect that AI-based education will be deeply established around us in the near future. We first introduce the details of the personalization technology and then discuss the AI-based foreign language speaking education research conducted by ETRI.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.49-58
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• 2011

Recently, GIS(Geographic Information System) has been developed to personalized service for providing the specialized services that is aimed to personal user based on mobile communication. The existing GIS system provides comprehensive and simple information but GIS System for personalized service must provide the adjustive information through the personal interest profile based on POI(PoInt of Interest). This paper describes the intelligent retrieval geographical information service module for providing personal oriented geographic information service. Our proposal model consists of user preference profile, acquisition of POI through hybrid network (Wireless LAN, CDMA), service platform and implementation of prototype system. Implementation model can apply to the life information service like restaurant, oil station, convenient store and etc.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.147-153
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• 2014

To create a personal menu, there are a number of considerations. Personal menus are different depending on the dietary therapy for disease, diet for weight control. In addition, the menu you choose, depending on the personal preference and the season, the weather, current personal feelings may differ. An individual should expect to recommend a balanced diet, taking nutritional status just for health care. In this paper, we propose a personalized menu recommendations System framework to meet such needs. To recommend menus the system receives data of the body's individual circumstances, ingredients situation, environmental conditions, psychological condition, emotional condition and provides a recommended menu by performing the inference using the ontology generated from external application systems. In order to provide such services, Internet of Things (IoT) environment should be the foundation. In this paper, we propose a personalized diet recommendation system framework in the IoT standardization environment that has oneM2M common service platform.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.321-332
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• 2007

The digitalization of a broadcast has caused the oversupply of the contents in order to fit the user's needs for various broadcast services. The massive contents could not help demanding one-sided watching without considering a taste and preference of a user. This situation is enlarging the demand about the personalized broadcast service to enable user to watch broadcast contents in anytime according to surplus provision of broadcast contents. TV-Anytime standard could be a solution for broadcast service to enable users to watch personalized broadcast contents according to their preference. The paper proposes the personalized broadcasting system for authoring, receiving and transmission of TV-Anytime metadata, the detailed information about the broadcast contents so that user could efficiently search a large of broadcast contents stored in the PDR(Personal Digital Recorder)receiver under the DCATV(Digital Cable Television) environment.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.80-89
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• 2009

The importance of personalized services has been attracted in smart home environments according to the development of ubiquitous computering. In this paper, we proposed the smart home personalized service system based on context information using the speech recognition. The proposed service consists of an OSGi framework based service mobile manager, service manager, voice recognition manager, and location manager. Also, this study defines the smart home space and configures the commands of units, sensor information, and user information that are largely used in the defined space as context information. In particular, this service identifies users who exist in the same space that shows a difficulty in the identification using RFID through the training model and pattern matching in voice recognition and supports the personalized service of smart home applications. In the results of the experiment, it was verified that the OSGi based automated and personalized service can be achieved through verifying users in the same space.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.37-45
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• 2013

In this paper proposes the latest network-assisted online telemedicine service to coincide with the point being discussed for health care providers to match patients, patients with personalized medical service support system. In order to design the system, to understand the requirements of the patient personalized medical support service system, the data were normalized and were designed architecture client server structure. Further, in order to implement the system that was designed to define the structure of server and client, ontology repository, we implement the system. In this paper, as a result of the test by creating a scenario and prerequisites for testing patient personalized medical service support system that is design and implementation, selecting a patient's condition, department of symptoms by the selected but it was confirmed that the inference is, inference medical institutions that fits department inferred one following upon the items medical patient has the required.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.1-9
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• 2010

Diabetes is a type of metabolic disease presented by high blood sugar and that leads to significantly decrease the quality of life causing various symptoms. It is essential to manage a systematic menu for preventing such diabetes even though there are some ways for it including diet, physical exercise, medicinal prescription, and so on. This study proposes a smart phone based personalized menu management system for achieving the systematic diabetes management. At the present time almost menu systems for diabetes patients are subjectively prescribed by dietitians or doctors and that does not reflect current situations and personal preferences. The system proposed in this study provides the menu for diabetes patients according to season, weather, time, and personal preferences. In particular, the recipe and personalized menu for patients can be provided without limiting any time and location based on smart phone services, and its menu can easily be changed or selected by the phone.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.135-144
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• 2010

U-City pursues personalized service by collecting contexts through sensors located over the city and presenting the service automatically depending not on the user's request but on the situations that are needed. To provide the personalized service, however, contexts collected through various sensors are needed, and they include private information. Therefore, it is important to keep a balance between the convenience by presenting service and protecting private information. In this paper, we classify and grade person's various contexts requested in the personalized service environment. Based on these, we make decisions on whether to present the service or not by profile-matching between user profile and service profile. Also, we propose an efficient privacy-protection management scheme to encrypt transmitted private information and to control key distribution.