• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1091-1097
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• 2015

Internet-of-Things (IoT) becomes one of the most promising future paradigms, which foresees enormous amounts of interoperable things and heterogeneous services. The goal of IoT is to enable all things connected and brings all kinds information and services to people. However, such a great deal of information may lead to cognitive overload or restrain in productivity of people. Thus, it is a necessity to build intelligent mechanisms to assist people in accessing the information or services they needed in a proactive manner. Most of previous related mechanisms are built on well-defined web services and lack of consideration of constrained resources. This paper suggests a services composition method by adapting a hierarchical model, which is a graph-based model composed of four layers: Context Layer, Event Layer, Service Layer and Device Layer. With a such multi-layer graph, service composition can be achieved by the iteration of layer by layer. Then, to evaluate the effectiveness of this proposed hierarchical model, a real-life emergency response dataset is applied and the experimental results are composed with the general probabilistic method and indicate that the proposed method is help for compositing multiple services while considering given context and constrained resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2005-2014
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• 2008

In this paper, it is presented to utilize UPnP as RFID service discovery and control mechanism for context-aware services. Using UPnP, it is possible to achieve easy deployment of context-aware services and to provide zero-configuration for RFID services. In addition, SQL based cleaning module which raises detection rates is developed since context-aware applications heavily rely on streams of data gathered from RFID tags. Using the cleaning technique, detection rates are improved from 60-80% to 98% or more In order to verify RFID context aware service based on the UPnP, sample context-aware scenario for physical distribution services is implemented on UPnP over RFID system. The impacts of UPnP messages (or service advertisements on network congestion and SQL cleaning module are experimented and analyzed, and the result show the good correctness and validity of the proposed system.

• Journal of the Society of Disaster Information
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• v.5 no.2
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• pp.76-85
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• 2009

SWE(Sensor Web Enablement) is the standard platform of OGC for the sensor data service. SWE is only focusing in the data transmission protocols, but supporting the semantic decision. Sensor data service is the decision service of the status whether is on normal or not. In this study, we study the semantic decision model of the sensor data. It can support the context-aware service based on the decision information.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.199-220
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• 2015

Recently, many internet users are using mobile music service. In this paper, we aim to examine the effects of system quality factors and relation quality factors on continuance intention in the context of mobile music service. In order to analyze the antecedents of continuance intention, we introduced independent variables such as ease of use, stability, trust, involvement and unity. We also consider customer value and customer satisfaction as mediators. For empirical analysis, we surveyed 240 users of mobile music service. We conduct PLS (Partial Least Square) analysis for SEM (Structural Equation Modeling). As a result, 8 of proposed 12 hypotheses were accepted. Especially, system quality, trust and unity show positive influence on customer satisfaction significantly. Involvement and unity are positively related to customer value. Customer value and customer satisfaction show positive influence on continuance intention significantly. The results of this research can be useful guidelines for mobile music service users and providers.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.411-422
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• 2009

The study seeks to explore essential factors that influence tourists' continual usage intentions to mobile tour information services. The variables such as characteristics of tour information service, accuracy, interactivity, context, ubiquitous connectivity, perceived usefulness, perceived ease of use were adopted from previous research and the hypotheses were developed on the basis of Davis's Technology Acceptance Mode(TAM). The survey was conducted by users who have previously experienced mobile tourism information service. Structural equation modeling was used to Investigate the relationships between the factors. The results showed that interactivity, context, perceived usefulness and perceived ease of use were found to have a positive impact on satisfaction. In particular, interactivity and context were found to be the most significant factors that influence reuse intentions. It suggests that increasing context and interactivity to make tourist trust about accuracy, ubiquitous connectivity is better than increasing perceived usefulness and perceived easiness. The identified factors that influence continual usage intentions on mobile services can be useful for analyzing the market trends and suggesting industrial guidelines of mobile services.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.1-9
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• 2010

The increasing popularity of mobile devices, such as cellular phones, smart phones, and PDAs, has fostered the need to recommend more effective information in ubiquitous environments. We propose the recommendation method for mobile contents service using contexts and prefetching in ubiquitous environment. The proposed method enables to find some relevant information to specific user's contexts and computing system contexts. The prefetching has been applied to recommend to user more effectively. Our proposed method makes more effective information recommendation. The proposed method is conceptually comprised of three main tasks. The first task is to build a prefetching zone based on user's current contexts. The second task is to extract candidate information for each user's contexts. The final task is prefetch the information considering mobile device's resource. We describe a new recommendation.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.529-536
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• 2004

Smart homes integrated with sensors, actuators, wireless networks and context-aware middleware will soon become part of our daily life. This paper describes a context-aware middleware providing an automatic home service based on a user's preference. The context-aware middle-ware utilizes 6 basic data for learning and predicting the user's preference on the multimedia content : the pulse, the body temperature, the facial expression, the room temperature, the time, and the location. The six data sets construct the context model and are used by the context manager module. The log manager module maintains history information for multimedia content chosen by the user. The user-pattern learning and pre-dicting module based on a neural network predicts the proper home service for the user. The testing results show that the pattern of an in-dividual's preferences can be effectively evaluated and predicted by adopting the proposed context model.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.121-144
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• 2004

Developing a personalized system on a user's behalf which is working around the Internet-based marketplace is one of the challenging issues in intelligent e-business, especially mobile commenrce. It has been highly recommended that such a mobile personalized system has to perceive the user's needs a priori by tracking user's current context such as location with activity and then to identify the current needs dynamically and proactively. Automatically and unobtrusively getting user's context is an inevitable feature for the development of autonomous mobile commenrce. However, personalization methodologies and their feasible architectures for context-aware mobile commerce have been so far very rare. Hence, this paper aims to propose a context-aware mobile commerce development methodology by applying agent and semantic web technologies for personalized reminder system, which is one of the mobile commerce support system. We revisited associationism to understand a buyer's need identification process and adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have showed how the agent-based semantic web service system can be used to realize need-aware reminder system. NAMA(Need-Aware Multi-Agent), a prototype system, has been implemented to show the feasibility of the methodology and framework under mobile setting proposed in this paper. NAMA embeds bluetooth-based location tracking module and identify what a user is currently looking at through her/his mobile device such as PDA. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services, to aware user's current needs and then link her/him to a set of services, which are implemented as web services.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.617-628
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• 2005

The services for ubiquitous computing environments have to provide automatically user-specific adaptive services in dynamically changed environments with many informations provided by both a user and his/her environment. Workflows used in business and distributed computing environments support service automation by connecting many tasks with rules or orderings of tasks. Therefore we must specify context information on transition condition to support context-aware services by adapting a workflow to ubiquitous computing environments. In this paper, we present a structural context model to specify context information on transition constraints of the workflow. And we propose an uWDL Ubiquitous Workflow Description Language) based on web services, which provides web service interfaces which are standardized and independent on heterogeneous and various platforms, protocols, and languages. The uWDL tan be interpreted and executed by a workflow engine, and provide users autonomic services based on context-awareness.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.59-68
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• 2016

Context-aware services recognize the context of situation environments of users and provide useful services according to the context for users. Usual rule-based systems can be used for context-aware services with the specified rules that express context information and operations. This paper proposes a light-weight rule engine that minimizes memory consumption for resource-constrained smart things. The rule engine manages rules at the minimum condition level, removes memories for intermediate rule matching results, and uses hash tables to store rules and context information efficiently. The implemented engine is verified using a rule set of a mouse training system and experiment results shows the engines consumes very little memory compared to the existing Rete algorithm with some sacrifice of execution time.