• 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.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.145-150
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• 2005

최근 전자상거래에 대한 관심과 투자가 집중되면서 효과적인 사용자 인터페이스인 대화형 에이전트에 대한 연구가 활발히 진행되고 있다. 기존의 대화형 에이전트는 사용자의 질의에 미리 준비된 답변을 제공하기 때문에 복잡한 대화 상황을 처리하지 못한다. 이런 한계를 극복하기 위해 베이지안 네트워크 등의 기법을 이용한 사용자 의도 추론 기술이 연구되고 있다. 본 논문에서는 기존의 정보검색을 위한 대화형 에이전트에서 사용자 의도 추론의 성능을 높이기 위해 노드간의 의미 관계를 표현하는 정보를 결합한 시맨틱 베이지안 네트워크(Semantic Bayesian Network; SeBN) 모델을 제안한다. 단발적인 질의 분석이 아닌 점증적 질의 분석 방법을 바탕으로 불충분한 정보로 적절한 답변을 추론하지 못할 경우에MII(mixed-initiative interaction)를 수행하여 주어진 문제를 해결한다. 실제 모바일 검색 사이트에 제안하는 방법을 적용하여 유용성을 확인하였다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.240-243
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• 2000

An apparel products retrieval system was proposed in which users can refer to products using Kansei evaluation values. The system adopts relevance feedback using history of the retrieval to learn the tendency of user evaluation. The system is based on a vector space retrieval model using products images expression as semantic scales. The system makes a query from user inputting information and retrieves closest products from the database. Revising algorithms of the difference method. linear multiple regression performed to investigate the effectiveness and criteria of the search. As a result of evaluation of the accuracy, it was found that the linear multiple regression and the neural network models are effective for the retrieval considering the individual Kansei.

• Knowledge Management Research
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• v.19 no.3
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• pp.47-61
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• 2018

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.346-353
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• 2011

With the advent of ubiquitous computing, a massive amount of trajectory data has been published and shared in many websites. This type of computing also provides motivation for online mining of trajectory data, to fit user-specific preferences or context (e.g., time of the day). While many trajectory clustering algorithms have been proposed, they have typically focused on offline mining and do not consider the restrictions of the underlying road network and selection conditions representing user contexts. In clear contrast, we study an efficient clustering algorithm for Boolean + Clustering queries using a pre-materialized and summarized data structure. Our experimental results demonstrate the efficiency and effectiveness of our proposed method using real-life trajectory data.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.432-438
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• 2007

이 연구는 정보 간의 관계에서 도출되는 특징을 적합하게 보여줄 수 있는 시각화를 위한 선행연구이다. 정보의 관계에 주목하는 이유는 관계 구조를 통해 정보의 성격과 특징을 파악할 수 있기 때문이다. 정보의 관계는 사회연결망 분석을 통해서 파악할 수 있다. 정보를 구성하는 개체와 개체 사이의 관계는 다양한 요소를 지니고 있으며, 연결망의 관계 분석 지표를 통해 관계의 성격과 특징을 도출해 낼 수 있다. 이 연구에서는 사회연결망에서 관계의 성격을 도출하는데 중요한 지표로 다뤄지는 영향력을 연구범위로 설정하고, 연결망 내의 관계의 요인과 영향력의 지표를 분류하고 연결한다. 이를 통해 사회연결망에서 영향력을 나타내는 관계의 요소를 중심으로 관계의 시각화 과정에 있어 적합한 시각화 프로세스를 온톨로지 개념을 사용하는 시멘틱 그래프에 적용해 보았다. 영향력의 각 관계 요소는 공통적인 개념과 성격, 측정 요소를 통하여 노드와 링크의 네트워크 형태의 그래프로 형성되었다. 영향력 시멘틱 그래프는 사회연결망의 영향력 요소를 이해하고, 분석하는데 유용하게 사용될 수 있음을 확인할 수 있다. 또한 시멘틱 그래프의 적용 범위를 연결망 시각화 전반을 확장하여, 합리적이고 효율적인 시각화 프로세스의 설정이 가능함을 알 수 있다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.609-610
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• 2006

This paper introduces a methodology for construction of ontology-based product knowledge Map. For CPC(Collaborative Product Commerce) environment, engineering application of ontology has been studied . However, there are no generic and comprehensive methodologies for ontology construction yet because of such problems: dependency on experience of ontologist and domain experts and insufficiency of detail stages or rules. To solve those problems, we propose a methodology to construct ontology from engineering documents in semi-automatic. We use middle-out strategy and term's axioms, sub-definitions, to build ontology map. 5-turple ontology structure, semantic network and First order logic (FOL) are used for ontology definition in this study.

• English Language & Literature Teaching
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• v.11 no.2
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• pp.149-170
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• 2005

The purpose of this paper is to make a sentence systemic within the category of structural grammar for the modality in which a speaker expresses his attitude. It is the priority of a language to communicate meaning. By eliminating the theoretical description of traditional grammar, this paper also aims to illustrate the concepts of nine modal verbs through a systemic network. The concept of modality includes both the epistemic and the deontic characteristics of modality. Epistemic modality is associated with either knowledge or belief on the part of a speaker who gives his own judgments about the state of affairs, events, or actions. However, deontic modality is related to either the possibility or the necessity of acts that a speaker performs to give permission or fulfill an obligation. In conclusion, all the subsystems are described within the framework of the systemic network, with the intention of including all the potential options of the semantic functions available in a situation.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.712-718
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• 2021

Virtual communities are studied to analyze their characteristic features, types, and tole to modern society. The article is aimed at creating a classification of virtual communities according to specific characteristics, which can be used to model the interaction, and necessity of components that are important for the community. The classification of virtual communities will contribute to their better performance and satisfy the users' needs in information. The study reveals the value structure of virtual communities, educational and communicative influence, and the possible threats these communities may bring to society and security.

• International Journal of Contents
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• v.15 no.1
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• pp.1-9
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• 2019

Since the VR market is expected to have a high growth, this study aimed to investigate the human factor-related determinants of user satisfaction with mobile VR headsets. A pre-study of customer reviews was conducted with the help of semantic network analysis to identify the core keywords for understanding negative and positive predictors of mobile VR headset experiences. Through laboratory testing with three different commercial models, the main study measured and identified the predictors of user satisfaction. From the results, five factors were extracted as valid predictor variables and used for regression analysis. These factors were immersion, VR sickness, usability, wear-ability and menu navigation interface. All the five predictors were proved to be significant determinants of the perceived user satisfaction with mobile VR headsets. Usability was the strongest predictor, followed by VR sickness and wear-ability. Practical and theoretical implications of the results were discussed.