• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.21-26
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• 2008

It was already realized at a current technological level of home network systems that the systems recognizes a user's simple order and carry out the order in the ubiquitous computing environment. However home is not a simple environment consisting into a large number of family members, so various order and situation would be needed accordingly. From now on we need to reach the technological level to infer that how is the user's behavior patterns and what kinds of service is the fittest to user who belong to the ubiquitous computing environment by using the result of the context interpreter. In this regards, active inferred-model needs to be suggested upgrading user's command into one step more higher level than the simple one adapting diversified feature. This study would like to suggest this active model recognizing context, which is user's environmental information applying basic network and inferring Context-based Service that user wants through the recognized result This study proposes a new method that can infer the user's desire in ubiquitous computing environment. First of all, we define a context as user's information of ubiquitous computing environment situation that user belongs to and we classify the context into 4W1H(Where, Who, When, What) formats. We construct Bayesian network and put the factor of context use as Bayesian network nodes. As a result, we can infer the user's behavior pattern and most proper service for user in the intelligent space from the probabilistic result of Bayesian network.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.119-126
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• 2009

In recent years, many recommendation service systems that search or recommend information automatically considering user's taste or property are developed. However, there is a weak point that correct recommendation is hard without considering the preference of user's context. This paper proposes a filtering method that gives correct recommendation considering the preference of user's context. To support this method, we get UCOP(User-Context Object Preference) using the preference of user's context and Pearson correlation coefficient. The results of the experiment show the improvement of 11%, 2% of precision and 8%, 4% of recall comparing with the existing service systems. Our recommendation service systems show 77% of precision and 53% of recall overall.

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

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.673-676
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• 2009

In this paper, we describe CAMAR Companoin, a context-aware mobile AR system that provides a user-adaptive assistance with an augmented picture according to the user's context in smart space. It recognizes physical objects and tracks the movement of those objects with a camera embodied to a mobile device. CAMAR Companion observes a mobile user's context, which is sensed by various kinds of sensors in environments, and infers user preference for the content in the situation. It recommends multimedia content relevant to the user's context. It overlays selected content over associated physical objects and enables the user to experience the content in a user-centric manner. Furthermore, we have developed the prototype to illustrate how our system could be used for a mobile user's well-being care applications in smart home environments. In this application, we found that our system could perceive a user preference even though a user's context is changed dynamically, and then adapt the multimedia content with respect to the user's context effectively. As such, the proposed user-adaptive system has the potential to play an important role in developing customized user interfaces in mobile devices.

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

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.346-350
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• 2009

According to the development of information technology, there are many services in our life. These services make our life safe and convenient. However, the increment of the services also causes the increment of human concern and effort to control these services. The context-aware service is the service that provided their functionality at the right time and to the right place by analysis user's current situation. The most previous studies about context-aware service regard that context-aware services are defined by the developer who has expertise in information technology. The definition of the context-aware services by the developer makes difficult to reflect user's personal preferences and life pattern to the services. In this paper, we propose an user interface EUCAS(by End-User, Context-Aware Service development) that make the user can define and manage their own context-aware service according to their preferences. We expect EUCAS can be effective user interface technology for providing personalized context-aware service.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.69-76
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• 2015

User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.301-307
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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 '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.

• 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.

• IE interfaces
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• v.21 no.1
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• pp.65-74
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• 2008

In the future, the ubiquitous computing environment will provide users with context-aware services, intelligently interacting with omnipresent resources and surrounding environments at any location and time. Therefore, the ubiquitous computing environment requires context-aware applications in order to gather and analyze context information in various situations. However, existing context-aware applications have mainly focused on providing services and adapting themselves to users based on user related contexts. But this environment requires not only user related contexts but also Quality-of-Service (QoS) related contexts. In this paper we propose a frame-work for supporting user-oriented QoS in ubiquitous environments. The proposed approach adopts a semantic ontology and a neural network algorithm in order to reason about explicit and uncertain contexts. We also show the possibility of applying the framework to real environments such as collaborative engineering service, automobile maintenance service and ubiquitous home service.