• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.129-157
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• 2016

This study investigates speech perception in noise (SPIN) in Korean. A new type of Korean SPIN test was developed by adopting a similar format to the English SPIN test. The predictability effects, noise effects and their interactions were examined in order to verify the previous findings based on English. The data from 14 Korean adults collected with this new type of Korean SPIN test confirmed the previous findings: first, the participants' overall performance was better in low noise conditions than in high noise conditions. Secondly, there was a tendency for highly predictable words to be more accurately perceived than less predictable words especially in high noise conditions. The results were interpreted in such a way that the listeners actively used both types of information: acoustic information and contextual information in speech perception. When the acoustic property of the speech sound was degraded with noise, the listeners took advantage of the linguistic contextual information in their processing of the speech sound. The findings of this study conform to those of the previous studies based on the English SPIN test. In addition, a possible effect of the frequency of target word was also found, calling for further investigation in this field of research in Korean. Implications of the results were also discussed. (Cyber Hankuk University of Foreign Studies)

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.650-657
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• 2006

The music is a part of our daily life in these days. And when the people listen to the music, they are affected by the context. However, previous researches on the music recommendation system have the problem that they didn't consider the proper contextual information efficiently. They only used the content-based filtering or the method to use musical metadata (genre, artist, etc.). Recently, there are some researches about the music recommendation system which applies the status(temperature, humidity, etc.) of environments. But, it is difficult to be accepted by the contextual information. Therefore, we propose the music recommendation system that is dynamically applied by the contextual information as well as the metadata in the previous researches. And the system can provide users with the music that they want to listen to, and then the users can be more satisfied. Also, the services can be improved by the feedback of the users. In order to solve this problem, the context-information for selecting a music list is defined and the music recommendation system is designed by using the content-based filtering method. The system is suitable for the user's taste and the context. The music recommendation system we are proposing uses an OSGi framework in the home network. As a result, the satisfaction of users and the quality of services will be improved more efficiently by supporting the mobility of services as well as the distributed processing.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.313-329
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• 2014

This study aims to provide intellectual access to TV content using faceted classification. In order to describe the content of news and current affairs programs, a faceted approach was explored. Based on the Ranganathan's PMEST formula, the basic facets - 'who', 'what', 'how', 'where', 'when' - and their sub-facets were created, specifically for describing the news genre. Additionally, the formal structure and the contextual features of the news genre were mainly considered for creating sub-facets. These created facets were applied to a news genre program. The result shows that these suggested facets are useful for representing well the contextual components of the news genre. The application of faceted classification is expected to improve the identification of the specific TV content.

• ETRI Journal
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• v.34 no.5
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• pp.743-752
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• 2012

Semantic interpretation of the relationship between noun compound (NC) elements has been a challenging issue due to the lack of contextual information, the unbounded number of combinations, and the absence of a universally accepted system for the categorization. The current models require a huge corpus of data to extract contextual information, which limits their usage in many situations. In this paper, a new semantic relations interpreter for NCs based on novel lightweight binary features is proposed. Some of the binary features used are novel. In addition, the interpreter uses a new feature selection method. By developing these new features and techniques, the proposed method removes the need for any huge corpuses. Implementing this method using a modular and plugin-based framework, and by training it using the largest and the most current fine-grained data set, shows that the accuracy is better than that of previously reported upon methods that utilize large corpuses. This improvement in accuracy and the provision of superior efficiency is achieved not only by improving the old features with such techniques as semantic scattering and sense collocation, but also by using various novel features and classifier max entropy. That the accuracy of the max entropy classifier is higher compared to that of other classifiers, such as a support vector machine, a Na$\ddot{i}$ve Bayes, and a decision tree, is also shown.

• Korean Journal of Adult Nursing
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• v.20 no.5
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• pp.707-718
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• 2008

Purpose: The present study was designed to understand the conceptual definition and attributes of the clinical critical thinking ability(CCTA) in nursing and to grasp the characteristics of clinical critical thinking abilities. Methods: The data were analyzed using the Hybrid model of Schwartz-Barcott and Kim(2000). Results: Having the skills and dispositions to think critically, CCTA refers to something that implies the cognizant ability to interpret contextual meanings, analyze the relationships between materials or circumstances, draw out the best conclusions, predict things using relevant information and evaluate the reliability of information and the strength of inference on the one hand and the emphatic disposition to be curious, open-minded, intellectually integral, systematic and creative and to reflect on things in contextual terms on the other. Conclusion: CCTA is characterized by clinical circumstances, such as guessing the reasons for facts, predicting things, connecting theory to practice and approaching individual situation in total terms as well as by the Korean circumstances, such as taking another person's perspective. Hence, this study proposes developing the tools to measure the clinical critical thinking ability and the strategies to improve the clinical critical thinking ability and seeking to verify their validity, on the basis of the findings.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.19-30
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• 2010

It has become important to have some proper guidelines of how to provide public transport information services in response to the rapid IT developments and the wide spread of public information services. The current study takes a contextual approach to the analysis of public transportation information use under a dynamic decision situation, complementing the conventional cross-sectional approaches. Using the CHAID of decision tree induction based on decision table formalism applied to the survey data of activity travel and information use, the study found that the information type and medium choices are strongly affected by the decision contexts in addition to the individuals' socio-demographic characteristics. The results suggest an important implication to the market segmentation of information services for public transportation.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.387-392
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• 2016

Context-aware systems require sensor data collecting model and context representing model to provide user-demand services. Sensor data collecting model consists of sensor access information, sensor value, and definition of value types. Context representing model involves certain keywords to symbolize environmental information including the field from sensor data collecting model that is described in markup language such as XML. However, duplicated keywords could be assigned to different contextual information by service developers. As a result, the system may cause misunderstanding and misleading wrong situational information from unintended contextual information. In this paper, we propose a context classification model for collecting appropriate access information and defining the specification of context.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.1-23
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• 2011

The contextual subjective well-being (SWB) of context-aware system users can be very helpful in recommending relevant mental health services, especially for those who struggle with mental illness due to a metabolic syndrome or melancholia. Self-surveying measuring or auto-sensing methods have been suggested to monitor users' SWB. However, self-surveying measuring method is not inappropriate for a context-aware service due to requesting personal data in a manual and hence obtrusive manner. Moreover, auto-sensing methods still suffer from accuracy problem to be applied in mental health services. Hence, the purpose of this paper is to propose a contextual SWB estimation method to estimate the user's mental health in unobtrusive and accurate manners. This method is timely in that it acquires context data from the user's literal responses, which expose their temporal feeling. In particular, we developed a measuring method based on exposed feeling verbs and degree adverbs in chat and other text-based communications which show anger or negative feelings. Based on the proposed contextual SWB degree estimation method, we developed an idea of well-being life care recommendation. From the experiment with actual drivers, we demonstrated that the proposed method accurately estimate the user's degree of negative feelings even though it does not require a self-survey.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.141-149
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• 2004

Today there are many Web courseware systems for formative evaluation and feedback. Formative evaluation and feedback provided according to users' response in most Web courseware systems, however, are simple texts showing only whether correct or wrong, correct answers, relevant information, etc., far deviated from actual context. Thus such a system may weaken the corrective function of feedback and, as a result, reduce learners' understanding of contents and the possibility of learning transfer. In addition, according to the learning theory of constructivism, learning is influenced by the situation, in which it happens, and knowledge is learned and transferred differently depending on the context in which it is learned. In the background, this study designed and implemented a contextual error-correction feedback system that can provide feedback in a context closely related and similar to the relevant situation according to the response of learners when formative evaluation is carried out in Web courseware. In addition, it applied 'correction/correct-answer-providing feedback', 'relevant information providing feedback' and 'contextual error-correction feedback' to Web courseware for learning actual productivity S/W and verified if 'contextual error-correction feedback' is more effective than other two types of feedback for learners' academic achievement.

• Information Systems Review
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• v.22 no.2
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• pp.167-199
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• 2020

The ICT-based curation as a series of experiences with the mobile exhibition-guide applications or guide programs in art galleries helps visitors fully immersed in the exhibition and allows them to have more informative and convenient guide experience at art galleries. This study aims to verify how the factors of ICT-based curation affects the commitment and satisfaction of visitors at art galleries, figure out whether the visitors' commitment has effects on their satisfaction, and then finally test the impact of their commitment and satisfaction on their revisit intention. In order to validate the cause-and-effect relationships between these factors, the ICT-based curation in this paper is categorized into five factors - gamification, quality of image/video information, quality of sound/text information, contextual offer, and instant connectivity. The main results of the study are as follows. First, only the gamification has significantly positive effects on the commitment of art gallery visitors, while other two factors - the instant connectivity, and the quality of sound/text information - have significantly positive effects on the satisfaction of visitors. Second, the commitment of visitors also has significantly positive effects on their satisfaction. Third, the commitment of the visitors don't have significantly positive relationship with their intention of revisit, but the satisfaction of the visitors have significantly positive relationship with their intention of revisit.