• Journal of IKEEE
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• v.11 no.4
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• pp.279-282
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• 2007

In this paper, we introduce the general way for producing context information to support context-aware applications. It can fetch raw data from the service environments, translate it to reasonable context information, and provide to multiple applications. It is designed originally for the ubiquitous computing middleware and based on the ontology processing model. Automated service applications can use this system as the form of libraries or of web services for deciding its semantic cause of action.

• Annual Conference on Human and Language Technology
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• 1994.11a
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• pp.326-332
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• 1994

본 연구에서는 중사전 규모의 현대국어사전에서 약 5,000 개의 표제항목의 뜻풀이 8,000여 항에 사용된 어휘를 분석한 결과를 제시하였다. 분석 결과 명사류의 의미구조에서 최상위계층에 속하는 것들이 사전의 뜻풀이에 자주 사용됨을 확인할 수 있었고, 아울러 뜻풀이에 사용되는 단어들이 어느 정도 통제된 상태임을 알 수 있었다. 그러나 표제항목과 뜻풀이에 사용된 단어들 사이의 관계만을 바탕으로 해서는 의미망을 구축하기 어려웠는데, 그것은 국어사전에서의 뜻풀이가 지니고 있는 구조적 문제에서 기인하는 것이다. 즉 일부 한자어의 경우에는 명사로 정의되지 않으며, 그 결과 표제명사와 뜻풀이에 사용된 명사 사이의 관계를 바탕으로 한 의미망의 구축에 포함되지 않는 것이다. 또한 순환적 뜻풀이의 경우 역시 의미망 구축에 장애요소로 작용함을 밝혔다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.266-268
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• 2011

스마트폰을 비롯한 모바일 기기에 내장된 다양한 센서들로부터 수집되는 개인의 일상에 대한 정보인 모바일 라이프로그를 관리하고 검색하는 다양한 연구가 진행되고 있다. 기존에는 에피소딕 메모리 형태로 저장된 모바일 라이프로그 상에서 사용자가 과거 정보를 찾고 회상하는 방법이 일반적으로 사용되었다. 이러한 방법에서는 사용자가 원하는 데이터를 찾기 위해서는 정확하고 충분한 데이터를 사전에 알고 있어야 한다. 하지만 사람은 처음부터 완전한 정보를 가지고 검색을 하는 것이 아니고 검색을 수행하면서 데이터간의 연관도를 바탕으로 추가적인 정보를 떠올리는 연관 검색을 수행한다. 본 논문에서는 연관도 기반 검색을 위해 인지구조를 바탕으로 모바일 라이프로그를 표현하는 시맨틱 네트워크를 자동으로 생성하는 방법을 제안한다. 정의된 구조를 바탕으로 네트워크를 구성하고 관계의 빈도수와 가중치 공유를 통하여 관계의 가중치를 학습한다. 구성된 시맨틱 네트워크상에서 활성화 확산을 기반으로 연관 검색을 수행함으로 방법의 유용성을 입증하였다.

• Science of Emotion and Sensibility
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• v.8 no.1
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• pp.1-7
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• 2005

This paper reports several emotion detecting methods based on various attributes of human voice. These methods have been developed at our Engineering Systems Laboratory. It is noted that, in all of the proposed methods, only prosodic information in voice is used for emotion recognition and semantic information in voice is not used. Different types of neural networks(NNs) are used for detection depending on the type of voice parameters. Earlier approaches separately used linear prediction coefficients(LPCs) and time series data of pitch but they were combined in later studies. The proposed methods are explained first and then evaluation experiments of individual methods and their performances in emotion detection are presented and compared.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2115-2127
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• 2021

Although significant progress has been made in synthesizing visually realistic face images by Generative Adversarial Networks (GANs), there still lacks effective approaches to provide fine-grained control over the generation process for semantic facial attribute editing. In this work, we propose a novel cross channel self-attention based generative adversarial network (CCA-GAN), which weights the importance of multiple channels of features and archives pixel-level feature alignment and conversion, to reduce the impact on irrelevant attributes while editing the target attributes. Evaluation results show that CCA-GAN outperforms state-of-the-art models on the CelebA dataset, reducing Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) by 15~28% and 25~100%, respectively. Furthermore, visualization of generated samples confirms the effect of disentanglement of the proposed model.

• Annual Conference of KIPS
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• 2010.11a
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• pp.1780-1783
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• 2010

본 논문은 P2P기반의 Query Rewriting을 이용한 멀티 에이전트 시스템을 제안하였다. 제안된 시스템은 Query Rewriting을 이용해 P2P의 이기종간 데이터 의미충돌 문제에 초점을 맞춰 데이터 상호 운용성을 높였다. 그리고 메타데이터 표현에 대한 매커니즘과 P2P 온톨로지 매핑, 그리고 질의응답에 대한 기법을 제시하였다. 또한 MSO(Meta Semantic Ontology)에 매핑을 표현 하기위해 Map을 이용하였고, 로컬 데이터 소스의 이질성을 고려한 Query Rewriting 기법을 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2483-2494
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• 2024

Instance segmentation is a challenging research in the field of computer vision, which combines the prediction results of object detection and semantic segmentation to provide richer image feature information. Focusing on the instance segmentation in the street scene, the real-time instance segmentation method based on SOLOv2 is proposed in this paper. First, a cross-stage fusion backbone network based on position attention is designed to increase the model accuracy and reduce the computational effort. Then, the loss of shallow location information is decreased by integrating two-way feature pyramid networks. Meanwhile, cross-stage mask feature fusion is designed to resolve the small objects missed segmentation. Finally, the adaptive minimum loss matching method is proposed to decrease the loss of segmentation accuracy due to object occlusion in the image. Compared with other mainstream methods, our method meets the real-time segmentation requirements and achieves competitive performance in segmentation accuracy.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.143-157
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• 2008

Ubiquitous Web Services is able to be specified future Web Services technology for connecting with various application services in any device and network environments. The devices, in ubiquitous environment, have dynamic characteristic such as location and statuse. So, we must support methods of dynamic service discovery in ad-hoc network. There are many related works at transaction, security, QoS, semantic and Web Services composition with various fields. Recently, the studies are interested in the Ubiquitous by development of computing and network technology. However, they are an early stage. For this reason, in this paper, we propose a WSUN(Web Services on Universal Networks) for Ubiquitous Web Services. It is a SOA based framework. And this paper extracts necessity of WSUN environment from scenario. The framework is composed of US Broker(Universal Service Broker). It is designed for satisfying the conditions and supports dynamic service discovery using a US Registry (Universal Service Registry). Consequently. clients are able to discover and use Universal Service by protocol stack of the US Broker for Web Services. And it is a strong point which supports interoperability between heterogeneous networks.

• The Research Journal of the Costume Culture
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• v.28 no.2
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• pp.265-284
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• 2020

This study aimed to analyze the performance of Disney-collaborated fashion lines based on online consumer reviews. To do so, the researchers employed text mining and network analysis to identify key words in the reviews of these products. Blogs, internet cafes, and web documents provided by Naver, Daum, and YoutTube were selected as subjects for the analysis. The analysis period was limited to one year after for the 2019. Data collection and analysis were conducted using Python 3.7, Textom, and NodeXL. The research terms in question were as follows: 'Disney fashion collaboration' and 'Frozen fashion collaboration'. Preliminary survey results indicated that 'Elsa's dress' was the most frequently mentioned term and that the domestic fashion brand Eland Retail was the most active in selling Disney branded clothing through its own brand. The writers of reviews for Disney-collaborated fashion products were primarily mothers with daughters. Their decision to purchase these products was based upon the following factors; price, size, stability of decoration, shipping, laundry, and retailer. The motives for purchasing the product were the positive response of the consumer's child and the satisfaction of the parents due to the child's response. The problems to be solved included insufficient quantity of supply, delay in delivery, expensive price considering the number of times children's clothes are worn, poor glitter decoration, faded color, contamination from laundry, and undesirable smells immediately after the purchase.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.672-678
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• 2008

Entities in reality have direct relationships between each other. They also have new and indirect relationships through such direct relationships. An ontology gives explicit meaning of such relationships. Thus, we can discover new relationships between entities based on an ontology. Such new relationships are applied in indentifying new communities or constructing social networks. Measuring for the degree of relationships is an important problem in such domains. This paper proposes a measurement for the degree of relationships between entities based on an ontology. Most of researches are based on connected paths between entities. However, there are meaningful relationships between two entities through the schema in an ontology even through there are no connected paths between the entities. The proposed method measures for the degree of relationships between two entities not based on connected paths, but also relationships through the schema. The experiment result shows that the relationships through the schema are meaningful to measure the degree of relationships between entities.