• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.11-14
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• 2009

In this paper, we propose the method configuring social networks among users based on users' context and profile. Recently, many researchers are concerned about social networks related with collaborative systems. In case of the existing researches, however, it is difficult to configure social networks dynamically because they are based on static data types, such as log and profile of users. The proposed method uses not only user profiles but also context reflecting users' behavior dynamically. It computes the similarity among users' behavior contexts using hierarchical structure of context domain knowledge model. And it calculates relationships between contexts by given weight factors of category of context model. In order to verify usefulness of the method, we conduct an experiment on configuring social network according to change of user context. We expect that it makes dynamic analysis of relationship of users possible.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.28-36
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• 2010

Some context is characterized by a single event in computing environment, but many other contexts are determined by a lot of things which occur with a space and a time. The Realtime Sensor Network context-awareness service that interacts with the physical space can have property such as time. A methodology that is specified the relationship between the contexts and the service needs to be developed to Realtime context-awareness deal with spatio-temporal. In this paper, we propose an approach which should include spatio-temporal property in the context model, and verify its effectiveness using enhanced Petri-Net. The context-awareness service modeling of Realtime Sensor Network is discussed the properties of model such as basic Petri-Net, patterned Petri-Net, or Spatio-temporal Petri-Net. The proposed methodology demonstrated using an example that is SAEMANGUEM warming watching system. The use of Spatio-temporal Petri-Net will contribute not only to develop the application but also to model the spatio-temporal context awareness.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.337-340
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• 2005

Context-awareness techniques in ubiquitous computing environment provide various services to users who need to get information via the analysis of collected information from sensors in a spatial area. Context-awareness has been increased in ubiquitous computing and is applied to many different applications such as disaster management system, intelligent robot system, transportation management system, shopping management system, and digital home service. Many researches have recently focused on services that provide the appropriate information, which are collected from Internet by different kinds of sensors, to users according to context of their surrounding environment. In this paper, we propose an abstraction model to manage the large-scale contextual information and their metadata which are collected from different kinds of in-situ sensors in a spatial area and are presented them on the web. This model is composed of the modules expressing functional elements of sensors using sensorML(Sensor Model Language) based on XML language and the modules managing contextual information, which is transmitted from the sensors.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.175-181
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• 2003

Because a word of Korean digits is a syllable and deeply coarticulatied in connected digits, some recognition models based on demisyllables have been proposed by researchers. However, they could not show an excellent recognition results yet. This paper proposes a recognition model based on extended and context-dependent demisyllables, such as a tri-demisyllable like a tri-phone, for the Korean 4-connected digits recognition. For experiments, we use a toolkit of HTK 3.0 for building this model of continuous HMMs using training Korean connected digits from SiTEC database and for recognizing unknown ones. The results show that the recognition rate is 92% and this model has an ability to improve the recognition performance of Korean connected digits.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.73-79
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• 2024

The smart tourism chatbot service provide smart tourism services to users easily and conveniently along with the smart tourism app. In this paper, the tourism information QA (Question Answering) service is proposed based on the task-oriented smart tourism chatbot system [13]. The tourism information QA service is an MRC (Machine reading comprehension)-based QA system that finds answers in context and provides them to users. The tourism information QA system consists of NER (Named Entity Recognition), DST (Dialogue State Tracking), Neo4J graph DB, and QA servers. We propose tourism information QA service uses the tourism information NER model and DST model to identify the intent of the user's question and retrieves appropriate context for the answer from the Neo4J tourism knowledgebase. The QA model finds answers from the context and provides them to users through the smart tourism app. We develop the tourism information QA model by transfer learning the bigBird model, which can process the context of 4,096 tokens, using the tourism information QA dataset.

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.6-14
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• 2006

The study investigates mental models of scientifically gifted, middle school students when it comes to tides. This was done by analyzing facet of conceptual types for two contexts. We carried out two performance tasks of tide with different context. A large number of students showed different conceptual types by context. As a result of analyzing facet of conceptual types by context, there was a slight difference in content-specific facet, but a remarkable one in strategic facet. We classified four mental models about tide by configuring facets of conceptual types: (1) Tide model (2) Force model (3) Phase model (4) Hybrid model. The Tide model is scientifically accepted model, but Force model and Phase model are incorrect models, and Hybrid model is mixed model. In cases of Force model and Phase model, conceptual types concur with each other, but these types of students comprehend tides as a result of joined forces of Moon & Sun and phase change of Moon, respectively. Arranging low mental models in proportional order, Tide model (45.0%), Hybrid model (30.0%), Force model (12.5%), and Phase model (7.5%).

• Journal of Families and Better Life
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• v.22 no.1
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• pp.103-114
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• 2004

This study was performed by the literature review on housing of the aged in Korea with social constructionism perspective. This kind of research may be utilized as a theoretical framework for performance of any systems of housing for the aged. In terms of structural context, the value of conventional custom of filial piety thoughts and duty for family are being collapsed, which nay be suitable to the change of society, should be considered for positive acceptance of changes in ideology. In terms of institutional context, a method to grope for housing for the aged should be established through amicable cooperation between organizations of legalization concerned. In terms of organizational context, there is no organization that exclusively concern housing for the aged until now, thus, development of concrete manual is required for jobs of service in current department of policy for the aged. In terms of operational context, the service may include the understanding of characteristics of the aged and design of housing may also change the service of administration, and as cooperation in the local community care systems may change the service to the aged in the field. Connection of these services and operation of these organizations nay be required in the field to manage housing. Finally in terms of intersubjective context, as the form and method of housing management service is important, with understanding of the social meaning and importance on the role of manager.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4B
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• pp.226-234
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• 2005

Context-Aware is the most important facts to reason a personalized and optimized service and to provide it to user. In the previous researches, user and surrounding environment were main facts of Context-Aware and middleware or center server has been proposed to support Context-Aware. In the daily space(for example, home, office, Car, etc), interactions between user and service can be a important facts of Context-Aware. In this paper, Context Autogenesis service model is introduced, simplified the Context-Aware process and designed the middleware which performs decentralize management for Context-Aware information of user's portable devices, so that problems occurred during the management and operation of existing Context-Aware system can be minimized and supporting user anonymity

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.63-69
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• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.867-878
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• 2021

In context awareness and user intention tasks, dataset construction is expensive because specific domain data are required. Although pretraining with a large corpus can effectively resolve the issue of lack of data, it ignores domain knowledge. Herein, we concentrate on data domain knowledge while addressing data scarcity and accordingly propose a multi-channel long short-term memory (LSTM). Because multi-channel LSTM integrates pretrained vectors such as task and general knowledge, it effectively prevents catastrophic forgetting between vectors of task and general knowledge to represent the context as a set of features. To evaluate the proposed model with reference to the baseline model, which is a single-channel LSTM, we performed two tasks: voice phishing with context awareness and movie review sentiment classification. The results verified that multi-channel LSTM outperforms single-channel LSTM in both tasks. We further experimented on different multi-channel LSTMs depending on the domain and data size of general knowledge in the model and confirmed that the effect of multi-channel LSTM integrating the two types of knowledge from downstream task data and raw data to overcome the lack of data.