• The Journal of Korean Association of Computer Education
• /
• v.8 no.4
• /
• pp.107-114
• /
• 2005

While a user is using an adaptive hypermedia system, the user can also use an external application. If the user accesses the information which is related to the contents provided by the adaptive hypermedia system, it can affect a user profile that contains the information about the knowledge or interests of the user. However, the adaptive hypermedia system understands user's behavior based on whether a page is accessed or not and it is difficult for the system to recognize user's behavior that can occur outside the adaptive hypermedia system. In this paper, we propose an approach that can detect user's behavior using a message hooking mechanism so that both user's behavior inside an adaptive hypermedia system and behaviors that occur outside the system can be reflected in a user profile. We analyze user events using a hooking mechanism and update a user profile using an XML parser.

• Journal of Korean Institute of Industrial Engineers
• /
• v.38 no.3
• /
• pp.173-181
• /
• 2012

The size and layout of user interface components need to be optimally designed in terms of reachability, visibility, clearance, and compatibility in order for efficient and effective use of products. The present study develops an ergonomic design method which optimizes the size and layout of user interface components using adaptive genetic algorithm. The developed design method determines a near-optimal design which maximizes the aggregated score of 4 ergonomic design criteria (reachability, visibility, clearance, and compatibility). The adaptive genetic algorithm used in the present study finds a near-optimum by automatically adjusting the key parameter (probability of mutation) of traditional genetic algorithm according to the characteristic of current solutions. Since the adaptive mechanism partially helps to overcome the local optimality problem, the probability of finding the near-optimum has been substantially improved. To evaluate the effectiveness of the developed design method, the present study applied it to the user interface design for a portable wireless communication radio.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.1
• /
• pp.55-60
• /
• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.

• Journal of KIISE
• /
• v.44 no.1
• /
• pp.27-35
• /
• 2017

Many studies have addressed 'Adaptive User Interface (AUI)', wherein the user interface changes in accordance with the situation and the environment of each user at runtime. Nevertheless, previous papers for AUI barely reflected the viewpoints from requirements engineering field, since most of them focused on proposing the architecture and design. In this study, we outline AUI with the perspective of requirements engineering and propose the requirements elicitation and specification method based on concepts which have been researched in the area of self-adaptive system. Step by step, we first redefine and reinterpret the well-known concepts of self-adaptive software, after which the AUI requirements are elicited and specified. Finally, we illustrate a case study, which demonstrates the effectiveness of our method.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.931-934
• /
• 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 KIISE:Software and Applications
• /
• v.31 no.4
• /
• pp.439-446
• /
• 2004

To design a user-adaptive web surfing system, we nay take the approach to divide the whole process into three phases; collecting user data, processing the data to construct and improve the user profile, and adapting to the user by applying the user profile. We have designed three software agents. Each privately works in each phase and they collaboratively support adaptive web surfing. They are IIA(Interactive Interface Agent), UPA(User Profile Agent), and ANA(Autonomous Navigation Agent). IIA provides the user interface, which collects data and performs mechanical navigation support. UPA processes the collected user data to build and update the user profile while user is web-surfing. ANA provides an autonomous navigation mode in which it automatically recommends web pages that are selected based on the user profile. The proposed approach and design method, through extensions and refinements, may be used to build a practical adaptive web surfing system.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.05a
• /
• pp.82-85
• /
• 2019

An adaptive power control scheme is proposed for the cognitive relay networks with joint overlay and underlay spectrum sharing model. The transmit power of the secondary user is adjusted adaptively according to the spectrum sensing results and the interference channel condition. The outage probability of the secondary user is compared by Monte - Carlo simulations between the fixed power control scheme and pure overlay or underlay spectrum sharing schemes. The results show that, by employing the adaptive power control strategy, the interference probability of the secondary user to the primary user is decreased by 70 % ~ 80 % under the same outage probability. Also, the outage probability of the secondary user is reduced by 1 ~ 2 orders of magnitude under the same interference probability. Thus, the performance of the spectrum sharing is improved effectively.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.573-578
• /
• 2008

Recently, we should control various devices such as TV, audio, DVD player, video player, and set-top box simultaneously to manipulate home theater system. To execute the function the user want in this situation, user should know functions and positions of the buttons in several remote controllers. Normally, people feel difficult due to these realistic problems. Besides, the number of the devices that we can control shall increase, and people will confuse more if the ubiquitous home environment is realized. Therefore, user adaptive interface that provides the summarized functions is required. Moreover there can be a lot of mobile and stationary controller devices in ubiquitous computing environment, so user interface should be adaptive in selecting the functions that user wants and in adjusting the features of UI to fit in specific controller. To implement the user and controller adaptive interface, we modeled the ubiquitous home environment and used modeled context and device information. We have used Bayesian network to get the degree of necessity in each situation. Behavior selection network uses predicted user situation and the degree of necessity, and it selects necessary functions in current situation. Selected functions are used to construct adaptive interface for each controller using presentation template. For experiments, we have implemented ubiquitous home environment and generated controller usage log in this environment. We have confirmed the BN predicted user requirements effectively as evaluating the inferred results of controller necessity based on generated scenario. Finally, comparing the adaptive home UI with the fixed one to 14 subjects, we confirmed that the generated adaptive UI was more useful for general tasks than fixed UI.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.9C
• /
• pp.826-833
• /
• 2007

In this paper, we present an adaptive transmission system model to establish the baseline for wireless adaptive transmission using CR (Cognitive Radio) systems, and propose an adaptive transmission scheme based on IT (Interference Temperature) cognition for CR systems in the presented system environment. The proposed CR adaptive transmission scheme is the method that provides the CR user with the maximum transmit power in the range of not causing any interference to the incumbent user and guaranteeing the optimal throughput by applying CR-AMC (CR-Adaptive Modulation and Coding) in the given channel state. Simulation results show that in case of using the proposed CR adaptive transmission scheme, there is little degradation of BER performance, while causing no interference to the incumbent user. At the same time, the proposed scheme guarantees the optimal throughput to the CR user in the given channel state.

• Journal of Broadcast Engineering
• /
• v.5 no.1
• /
• pp.94-101
• /
• 2000

User adaptive reception of broadcast programs includes the functionality such as the user adaptive filtering and browsing functionality. The user adaptive filtering means that the user can limit the list of programs to include only his/her favorite programs among hundreds of available programs. The user adaptive browsing means that the user can view a short summary of his/her selection in the way that he/she prefers. When the receiving system include the random access storage device, the automatic recording functionality of users favorite programs can be included. The user adaptive reception requires support from various meta-data such as user preference data and content description data. TV Anytime forum is a standardization effort to enable user adaptive TV reception, which means that the user can watch what s/he wants when s/he want in the way s/he wants. MPEG-7 includes not only the content description for broadcast applications but also other content descriptions such as structure information. This paper addresses the relationship between MPEG-7 and TV Anytime and investigates how MPEG-7 should be designed and be used to satisfy the requirements of the user adaptive reception of broadcast program.