• Journal of Digital Convergence
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• v.10 no.6
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• pp.253-258
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• 2012

In this thesis, I categorize expression of context data required for context data inference according to five Ws and one H(5W1H) in Ubiquitous computing environment and infer superordinate context by combining context data of 4W1H with inferred context of why. This thesis suggests that we categorize specific context and service according to 6W2H added Whom(specific data or service) and How much (accuracy), and determine proper services for specific contexts by introducing the concept of rough set for expression and inference of categorized contexts and inaccurate knowledge. Since there is an limitation of the set of 0 and 1 when concerned with accuracy of services, I introduce the concept of fuzzy set. To provide users with the most appropriate service by ridding of unnecessary properties through the process of reduction, I also use the concept of rough set.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.488-493
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• 2007

In general, recommendation systems quantify real-time context information obtained in the stage of collaborative filtering and use quantified context information in order to recommend services. But the recommendation systems can have problems of recommending inaccurate information because of lack of context information or classifying users into inaccurate groups because of simple classification works in the stage of quantification. In this paper, we solved the problems of lack of context information obtained in real-time by combining users' profile information used in the contents-based filtering and context information obtained in real-time. In addition, we tried collaborative filtering at the quantification stage by improving absolute classification methods to relative ones. As the result of experiments, this method improved prediction preference by 5.8% than real-time recommendation systems using context information in pure P2P environment.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.614-627
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• 2022

Aspect-based sentiment analysis is to discover the sentiment polarity towards an aspect from user-generated natural language. So far, most of the methods only use the implicit position information of the aspect in the context, instead of directly utilizing the position relationship between the aspect and the sentiment terms. In fact, neighboring words of the aspect terms should be given more attention than other words in the context. This paper studies the influence of different position embedding methods on the sentimental polarities of given aspects, and proposes a position embedding interactive attention network based on a long short-term memory network. Firstly, it uses the position information of the context simultaneously in the input layer and the attention layer. Secondly, it mines the importance of different context words for the aspect with the interactive attention mechanism. Finally, it generates a valid representation of the aspect and the context for sentiment classification. The model which has been posed was evaluated on the datasets of the Semantic Evaluation 2014. Compared with other baseline models, the accuracy of our model increases by about 2% on the restaurant dataset and 1% on the laptop dataset.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.641-649
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• 2017

As Internet of Things devices become pervasive, services improve to better assess the context and to alert other users to deal with emergencies. Such services use Internet of Things devices to detect the context around the user and promptly notify public institutions, hospitals or other parental users in emergencies. Most of these systems analyze an event when the value of the device is unchanged for a period of time or if it detects an abnormal value. However, just monitoring sensor values makes it difficult to accurately understand the context surrounding a user. Also if the device is inactive, it can not identify the context or provide services again. However, understanding the user requirements, services provided through other devices, information sent to other users lets, appropriate actions be taken. This paper, proposes a device search method and system based on a context-aware model that includes user demands. The proposed system analyzes the user's context and demands by using data collected from the internet of things devices. If user devices are inactive, they can recognize other devices by searching for other devices and providing services to users again. Through the proposed method, the user-centric services are provided. This method also analyzes and responds to requirements in various emergencies.

• Journal of the Korean Institute of Rural Architecture
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• v.22 no.3
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• pp.1-8
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• 2020

This paper takes Zhaoxing Dong village in Guizhou Province as the research object. The purpose is to study the continuity of landscape context in Dong Village. The research process includes specification on the evaluation system of Dong village landscape context by AHP method, and use of the questionnaire survey method in sequence, according to the specific situation of Zhaoxing Dong village, and this study develops a specific questionnaire that modifies the evaluation system suited to reflect specific problems. Through the analysis of the specific questionnaire and recycling in Zhaoxing Dong village, this study found that Zhaoxing Dong village as a whole is over commercialized due to the vigorous development of tourism service industry. As a result, whether it is experts, foreign tourists or local villagers, the rating of the village landscape is low. There are three problems in the village landscape context: historical continuity, invisible cultural heritage and contradiction in protection and development. The results of this paper provides a future direction for the protection and inheritance of Zhaoxing Dong village.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1282-1290
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• 2017

Since the mitigation of fear of crime significantly enhances the consumptions in a city, studies focusing on urban safety analysis have received much attention as means of revitalizing the local economy. In addition, with the development of computer vision and machine learning technologies, efficient and automated analysis methods have been developed. Previous studies have used global features to predict the safety of cities, yet this method has limited ability in accurately predicting abstract information such as safety assessments. Therefore we used a Convolutional Context Neural Network (CCNN) that considered "context" as a decision criterion to accurately predict safety of cities. CCNN model is constructed by combining a stacked auto encoder with a fully connected network to find the context and use it in the CNN model to predict the score. We analyzed the RMSE and correlation of SVR, Alexnet, and Sharing models to compare with the performance of CCNN model. Our results indicate that our model has much better RMSE and Pearson/Spearman correlation coefficient.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.152-155
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• 2002

In recent years, with the spread of communication media, such as a cellular phone and E-mail, we are able to communicate with others without any restriction of position or time. However, complexity of communicative context has increased so that user has to guess a partner user's situation and status in order to use various medias efficiently. This problem will grow larger as new media are brought in the expanding communications network. To solve this problem, we propose the system that guesses the context in communication by a user's media from the position information on PHS (Personal Handy phone System) and schedule information from schedule application. In this system a user's agent guesses automatically the context that owner has set, and answers the demand of the context from a partner user. Moreover, the agent decides a suitable answer, when there is a demand of communication by the media, which cannot be used.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.51-72
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• 2010

Given the extensive role of IS in everyday life and the increasing presence of women in IS users, understanding gender differences in individual technology continuance usage decisions is an important issue. Nevertheless, much of the large body of research on gender differences has just examined mean differences between women and men in terms of abilities, usage habit, and traits. Even though lots of psychology studies have shown that women, more than men, were influenced by affective factors, gender-affection-continuance use linkage has not been examined in the context of on-line shopping services. Therefore, the primary purpose of this paper is to seek to examine gender differences in terms of influence of affective factor in the context of IS continuance use. Meanwhile, IS continuance has been an important subject of study in the IT research area. To date, to explain why and how users are motivated to continue to use on-line shopping services, lots of theory-based research such as expectation-confirmation model (ECM) has been proposed. In particular, various affective factors have been proposed to explain continuance use of on-line shopping services recently. Affective factors have been regarded as essential factors for increasing relational strength and satisfaction. Several affective factors have been studied by prior IS adoption and continuance studies. Among them are enjoyment and anxiety. In IS continuance research, positive affect has been commonly and narrowly conceptualized and measured as the enjoyment which a person derives from using computers. Hence, in this study, we introduced intimacy factor, which was conceptually related to the quality of interactions and relationships in previous research. It also has been regarded as essential factors for strengthening human relationships. As a result, we have observed gender effect while examining intimacy-continuance bond. As expected based on the previous literatures, women seem to be more sensitive in affective factors. The contribution point here is that we find evidence in the context of on-line shopping services.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.104-108
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• 2007

Ad hoc networks are a type of mobile network that function without any fixed infrastructure. One of the weaknesses of ad hoc network is that a route used between a source and a destination is to break during communication. To solve this problem, one approach consists of selecting routes whose nodes have the most stable link cost. This paper proposes a method for improving the low power distributed MAC. This method is based on the context awareness of the each nodes energy in clustering. We propose to select a new scheme to optimize energy conserving between the clustering nodes in MANET. And this architecture scheme would use context-aware considering the energy related information such as energy, RF strength, relative distances between each node in mobile ad hoc networks. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.3
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• pp.129-137
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• 2015

Various personalized services are provided based on user context these days, and IoT(Internet of Things) devices provides effective ways to collect user context. For example, user's activity such as walking steps, calories, and sleeping hours can be collected using smart activity tracker. Smart scale can sense change of user's weight or body fat percentage. However, these services are independent to each other and not easy to make them collaborate. Many standard bodies are working on the documents for this issue, but due to diversity of IoT use case scenarios, it seems that multiple IoT technologies co-exist for the time being. This paper propose a framework to collaborate heterogeneous IoT services. The proposed framework provides methods to build application for heterogeneous IoT devices and user context management in more intuitive way using HTTP. To improve compatibility and usability, gathered user contexts are based on MPEG-UD. Implementation of framework and service with real-world devices are also presented.