• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.931-934
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• 2005

This paper describes an adaptive recommendation system that provides real-time personalized trading advice to the investors based on their profiles and trading information environment. A proposed system integrates Stochastic technical analysis and artificial neural network that incorporates an adaptive user modeling. The user model is constructed and updated based on initial user profile and recorded user interactions with the system. The information presented to each individual user is also tailor-made to fit the user's behavior and preference. A system prototype was implemented in JAVA. Experiments used to evaluate the system's performance were done on both human subjects and synthetic users. The results show our proposed system is able to rapidly learn to provide appropriate advice to different types of users.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.385-392
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• 2002

Collaborative filtering method for personalization can suggest new items and information which a user hasn t expected. But there are some problems. Not only the steps for calculating similarity value between each user is complex but also it doesn t reflect user s interest dynamically when a user input a query. In this paper, classifying users by their interest makes calculating similarity simple. We propose the a1gorithm for readjusting user s interest dynamically using the profile and Bayesian learning. When a user input a keyword searching for a item, his new interest is readjusted. And the user s profile that consists of used key words and the presence frequency of key words is designed and used to reflect the recent interest of users. Our methods of adjusting user s interest using the profile and Bayesian learning can improve the real satisfaction of users through the experiment with data set, collected in University s library. It recommends a user items which he would be interested in.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.257-264
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• 2012

The development of mobile devices and the spread of wireless network help share and exchange information and resources more easily. The bond them to Cloud Computing technology help pay attention to "Mobile Cloud" service, so there have been being a lot of studies on "Mobile Cloud" service. Especially, the important of 'Recommendation Service' which is customized for each user's preference and context has been increasing. In order to provide appropriate recommendation services, it enables to recognize user's current state, analyze the user's profile like user's tendency and preference, and draw the service answering the user's request. Most existing frameworks, however, are not very suitable for mobile devices because they were proposed on the web-based. And other context information except location information among user's context information are not much considered. Therefore, this paper proposed the context-aware framework, which provides more suitable services by using user's context and profile.

• The KIPS Transactions:PartC
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• v.9C no.6
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• pp.831-840
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• 2002

Due to the advance of computer and communication technology, intrusions or crimes using a computer have been increased rapidly while tremendous information has been provided to users conveniently Specially, for the security of a database which stores important information such as the private information of a customer or the secret information of a company, several basic suity methods of a database management system itself or conventional misuse detection methods have been used. However, a problem caused by abusing the authority of an internal user such as the drain of secret information is more serious than the breakdown of a system by an external intruder. Therefore, in order to maintain the sorority of a database effectively, an anomaly defection technique is necessary. This paper proposes a method that generates the normal behavior profile of a user from the database log of the user based on an association mining method. For this purpose, the Information of a database log is structured by a semantically organized pattern tree. Consequently, an online transaction of a user is compared with the profile of the user, so that any anomaly can be effectively detected.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.545-558
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• 2003

It is expected that per-user customized services are widely used in next generation Personal Communication Network. The ultimate goal for personalized service is the Virtual home Environment (VHE) providing ´same-look-and-feel´ services for the subscriber wherever he roams to. To provide personalized services for each call, per-user service profiles are frequently referenced, so efficient service profile management is essentially required. To realized the VHE, typically two schemes, can be employed; One is Intelligent Network based service control and the other is a full replication scheme that always replicates profile in user´s current zone. The first scheme is referred as Central scheme and th second scheme is the modified replication scheme of IMT-2000, we refer to as Follow-Me Replication Unconditional (FMRU). Since the Central scheme only depends on the service cal rate and the FMRU is merely dependent on the movement rate, it is apparent that FMRU scheme outperforms the Central scheme if the call to mobility ratio (CMR) is large, and vice versa. In this paper, we propose a new service profile replication schemes, Adaptive Follow-Me Replication (AFMR) that determine replication automatically according to the user´s CMR. We compared the performance of the AFMR with the non-adaptive Follow-Me Replication unconditional on Demand (FMRUD) scheme. Performance results indicate that as the CMR of a user changes AFMR adapts well compared to the existing schemes.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.455-457
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• 2000

3세대 통신망인 IMT-2000 서비스의 가장 큰 특징은 단말 이동성, 개인 이동성 및 서비스 이동성으로 구분되는 강력한 이동성의 제공이다. 이 중 서비스 이동성은 IMT-2000 서비스의 가장 큰 특징으로 가상 홈 환경(VHE ; Virtual Home Environment) 개념을 이용하고 있다. VHE는 개인 단말사이, 망 경계를 뛰어넘는 개인 서비스 환경 이동성의 개념으로 글로벌 로밍의 환경에서 서비스 가입자에게 Visited 망에서도 Home 망의 서비스를 그대로 이용할 수 있도록 하는 개념이다. 이 VHE에서 핵심이 되는 것이 프로파일을 어떻게 관리하여 사용자에게 원활한 서비스를 제공할 것인가 하는 것인데, 본 논문에서는 VHE 서비스를 위한 사용자 프로파일(User Profile), 서비스 프로파일(Service Profile), 단말 프로파일(Terminal Profile), 네트워크 프로파일(Network Profile)에 대한 관리 방법을 사용자 프로파일이 Home 망과 Visited 망에 위치하는 방법에 따라 시나리오에 적용하여 각 프로파일 정보를 교환하는 방법을 기술하였다.

• Journal of Korean Library and Information Science Society
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• v.35 no.4
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• pp.215-228
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• 2004

Discussion on the use of the library service should be based on both theoretical research and practical experiences. To increase the usage level of digital reference services in Korea, various aspects of the promotion, including latent user profile, publicity, site accessibility, and evaluation are examined, based on the previous research and overseas successful approaches. Results revealed useful information for planning and implementation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1364-1370
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• 2017

This paper proposes a method that automatically sets profile schedule context-based mobile phone by collecting the user's external situation based on the GPS sensor and accelerometer built into the smartphone and interacting with the data in the user's schedule to minimize the user's handset handling. However, real-time data collection in mobile phones causes energy shortage in the device due to battery consumption. In other words, a service control method is explained in a way that can efficiently handle resource consumption because accessing a measurement device such as GPS and other sensors may increase power consumption of the portable device. Therefore, effective data sharing for context awareness to reduce weekly schedules and smartphone mode has improved energy efficiency in sensing for data collection. The user can use the context more effectively by providing environmental adaptability for various situations such as the end user's local context and smartphone force control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1750-1755
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• 2011

Recently, it is possible for users to acquire necessary data easily as the various schemes of the searching information are developed. Since these data rise continuously like stream data, it is required to extract the appropriate data for the user's needs from the mass data on the internet. In the traditional scheme, they are acquired by processing the user queries after the occurred data are stored at a database. However, it is inefficient to process the user queries over the large volume of continuous data by using the traditional scheme. In this paper, we propose the Event-Profile Model to define the data occurrence on the internet as the events and the user's requirements as the profiles. We also propose and implement the filtering scheme to process the events and the profiles efficiently. We evaluate the performance of the proposed scheme and our experiments show that the new scheme outperforms the other on various dataset.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.