• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.4
• /
• pp.270-276
• /
• 2012

With the increase in amount of data and information available on the web, there have been high demands on personalized information retrieval services to provide context-aware services for the web users. This paper proposes a novel dynamic multi-agent context-awareness user profile construction method based on ontology to incorporate concepts and properties to model the user profile. This method comprehensively considers the frequency and the specific of the concept in one document and its corresponding domain ontology to construct the user profile, based on which, a fuzzy c-means clustering method is adopted to cluster the user's interest domain, and a dynamic update policy is adopted to continuously consider the change of the users' interest. The simulation result shows that along with the gradual perfection of the our user profile, our proposed system is better than traditional semantic based retrieval system in terms of the Recall Ratio and Precision Ratio.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.4
• /
• pp.270-275
• /
• 2008

Under ubiquitous environment, recommendation system is using the collaborative filtering methods by quantifying context information, but insufficient context information can cause inaccurate recommendation result. In order to solve such problems, the researcher used context information and user's profile. But service history information in users' profiles can have the problems of being influenced by change of the user's taste or fashion as time passes by. In addition, context information and user's profile can't be properly inter-locked according to situation, which can cause inaccurate predictability. In this paper, in case a user's taste or fashion is changed as time passes by, the researcher didn't apply bundled-up value to the user's profile but applied different weight according to change of time. And the researcher could solve the problem that context information and a user's profile can't be properly inter-locked according to situation by applying different weight to the result gained by means of collaborative filtering and then by unifying it. In such ways, the researcher could improve predictability.

• The KIPS Transactions:PartC
• /
• v.14C no.3 s.113
• /
• pp.293-304
• /
• 2007

In this paper, a client-side framework for processing of the profile that is necessary for providing adapted content to user's context in the client is designed and implemented. The profile must be constituted context information and various user's information for providing the adapted content to user's context. The client device also provides functionalities such as the creation, the management, and the transmission of the profile. The profile which is used in the proposed profile framework consists of various related information of a user for content adaptation. The technology such as creation, transmission and manage of the profile for effective processing is proposed and apply this technologies to client profile framework during the design are applied. As the result of evaluation, techniques of the proposed framework for processing profiles is more effective than previous techniques.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.5B
• /
• pp.542-551
• /
• 2009

We proposed the context based user profile which is aware of its user's situation and based on user's situation it recommends personalized services. The user profile which consists of (context, service) pair can be acquired by the context and the service usage of a user; it then can be used to recommend personalized services for the user. In this paper, we show how they can be evolved without previously known user information so that not to violate privacy during the learning phase; in the result our user profile can be applied to any new environment without any modification to model only except context profiles. Using context-awareness based user profile, the service usage pattern of a user can be learned by the union of contexts and the preferred services can be recommended by the current environments. Finally, we evaluate the precision of proposed approach using simulation with data sets of UCI depository and Weka tool-kit.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.3
• /
• pp.165-170
• /
• 2007

Recommendation systems provide users with proper services using context information being input from many sensors occasionally under ubiquitous computing environment. But in case there isn't sufficient context information for service recommendation in spite of much context information, there can be problems of resulting in inexact result. In addition, in the quantification step to use context information, there are problems of classifying context information inexactly because of using an absolute classification course. In this paper, we solved the problem of lack of necessary context information for service recommendation by using dynamic profile information. We also improved the problem of absolute classification by using a relative classification of context information in quantification step. As the result of experiments, expectation preference degree was improved by 7.5% as compared with collaborative filtering methods using an absolute quantification method where context information of P2P mobile agent is used.

• Journal of Korea Society of Industrial Information Systems
• /
• v.14 no.2
• /
• pp.1-7
• /
• 2009

This paper proposes a context gathering system that obtains user's environment information from sensor and generates user's context profile. To design the system, we classify context and design context model based on traditional context-aware computing. The proposed system supports contexts adaptation service by gathering user's environment characteristics and biological characteristics and generating user profile.

• Journal of Korea Multimedia Society
• /
• v.9 no.12
• /
• pp.1709-1718
• /
• 2006

Users are able to use the information and service more free than previous wire network due to development of wireless network and device. For this reason, various studies on ubiquitous networks have been conducted. Various contexts brought in this ubiquitous environment, have recognized user's action through sensors. This results in the provision of better services. Because services exist in various places in ubiquitous networks, the application has the time of services searching. In addition, user's context is very dynamic, so a method needs to be found to recommend services to user by context. Therefore, techniques for reducing the time of service and increasing accuracy of recommendation are being studied. But it is difficult to quickly and appropriately provide large numbers of services, because only basic context information is stored. For this reason, we suggest DUPS(Dimension User Profile System), which stores location, time, and frequency information of often used services. Because previous technique used to simple information for recommending service without predicting services which is going to use on future, we can provide better service, and improve accuracy over previous techniques.

• Journal of Digital Convergence
• /
• v.10 no.1
• /
• pp.301-307
• /
• 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 'Personalization Service' which is customized for each user's preference and context has been increasing. In order to provide appropriate personalization 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.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.901-904
• /
• 2014

As sensing techniques have advanced, context-aware technologies have been developed under the various domain for each different purpose. The number of services were created and are being used actually, but the services for specific spatial domain are not adequate yet. To solve this, there have been many efforts, and some of them were actually successful. Among them, the methods which used ontology-based inference were relatively reliable and appropriate for context-aware system, but not able to support contexts for individual without complex rules. In this paper, current scope of context inference is extended from user-oriented context modeling to entity-oriented. Furthermore, we used user profile and home profile to provide more specific context information of not only each individual but entity.