• International Journal of Contents
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• v.11 no.2
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• pp.63-68
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• 2015

A citation analysis utilizes the relations among citations and is the most popular bibliometric method. This analysis is based on 1) the evaluation by paper, journal and researcher of the research output, 2) the identification of emerging research topics, 3) the production of a map of the intellectual structure of the research domain and 4) various services for academic information. However, this approach has a limitation in that a citation is treated in a very simple manner, even though the purpose of citation can vary greatly. To address this problem, new approaches have been studied that take into account the citation context. This research separates the citations according to the citation functions and tries to conduct an analysis according to the newly classified citations. Furthermore, research on the citation summarization and visualization based on both the citation context and the citation function of the citations was also attempted. However, since there are very few studies related to citation context in South Korea, more research and development is needed in this area. This study analyzes the status of the research in terms of the citation context. For this, we utilized social network analysis methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.304-309
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• 2007

What is important in ubiquitous computing is collecting users' context information from various sensors and providing services suitable for use's current situation. Particularly in mobile environment, each area has different context awareness structure and this makes it difficult to share information with other areas. As a result, context resources for recognizing users' context ate insufficient. Moreover, because mobile devices have a limited processing capacity, there are difficulties in the real time analysis of users' context. This paper proposed a context awareness and integration model for analyzing users' context actively and providing adaptive services using mobile devices. The proposed model distinguishes users' context between dynamic and static structure to analyze the context, and obtains context resources by sharing context information of users within an area.

• Journal of Software Engineering Society
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• v.24 no.1
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• pp.19-26
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• 2011

Since smart phones have various embedded sensors and high portability/usability, they have emerged as suitable targets to collect information and to provide intelligent services. That is, with a smart phone, we can collect information about user's circumstances and phone usage from sensors and infer his/her current state which is the significant basis for context-aware services. However, a service system should be founded on a context model to ensure reasonable context-awareness, because context information the system needs depends on its target services. Therefore, in this paper, we propose a hierarchical mobile context model for context inference of smart phone users in their daily life. We classify high-level context which can be draw from sensing data into three levels, Context-Behavior-Situation, and define inference methods for each level. With our mobile context model, we can user's meaningful context in his/her daily life besides simple actions or states.

• Journal of Ubiquitous Convergence Technology
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• v.1 no.1
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• pp.47-52
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• 2007

In this paper, we present a virtual tourist system with realtime 3D visualization and the assistance of context information service. Our system enables a visitor to take a discovering tour on a virtual environment from a remote client by following navigator or by self-navigating. During the tour, the system provides immersive 3D graphics contents while supporting relevant information to the visitors corresponding to their positions in the virtual environment. When the visitors interact with interested objects, the context information service will also support introduction information for presenting about the objects. The introduction information based on text format is represented by a comfortable way-audio conversion to visitors in different languages depended on their preferences using TTS(Text-To-Speak) tool.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.432-434
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• 2000

본 논문은 IJG(Independent JPEG Group) JPEG 부호기의 처리 과정중 color table 과 context 버퍼를 이용한 color conversion과 downsampling 방법에 대해 소개한다. IJG JPEG은 전처리 과정에서 context buffer 사용함으로써 각 컴포넌트(RGB)에 대한 color conversion과 downsampling을 효과적으로 수행한다. 또한 각 컴포넌트(RGB)에 대한 부동 소수점 연산의 처리 결과를 미리 계산하여 color table에 저장함으로써 color converter에서 이를 참조, 색차 변환 계산에 적용하도록 하여 처리 속도를 향상 시키고 있다. 이에 본 논문에서는 IJG JPEG의 부호화 과정에서 사용되는 context 버퍼의 구조와 필요성 그리고 color table의 구조와 효과에 대하여 소개한다.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.115-125
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• 2007

The purpose of this paper is to propose a new type of NPI licensing context through French subjunctive and ne expletif. The distribution of NPIs on previous studies does not exactly correspond to negative function types. French subjunctive and ne expletif are good guidelines for reclassifying NPI licensing context. My classification is by a hierarchy of strength in negative force: overtly negative proposition > negative entailment > negative implicature. A new type of NPI licensing context is: (i) I-domain for negative implicature (ⅱ) E-domain for negative entailment and (ⅲ) overt negation.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1250-1260
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• 2020

This study proposes a novel deep neural network model that can accurately detect objects and their relationships in an image and represent them as a scene graph. The proposed model utilizes several multimodal features, including linguistic features and visual context features, to accurately detect objects and relationships. In addition, in the proposed model, context features are embedded using graph neural networks to depict the dependencies between two related objects in the context feature vector. This study demonstrates the effectiveness of the proposed model through comparative experiments using the Visual Genome benchmark dataset.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.205-211
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• 2012

In this paper, we proposed a context-aware augmented reality platform for mobile augmented reality to support user-oriented virtual world information for smartphone user. We designed the platform architecture and 6 subsystems which are derived from the analysis of existing augmented reality applications and platforms. The proposed architecture includes a context reasoning service subsystem for the context-aware information filtering, and separates the inner platform from the outer virtual world network containing virtual information to resolve interoperability issue of POI(Points of Interest) data.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.51-57
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• 2009

There are a variety of users and devices in a context-aware computing environment. In this environment, the service provided to a user may be the composition of diverse services rather than one independent service. Before user's devices provide the composite service to the user, they should perceive user's needs by gathering related information segments from other surrounding devices and/or sensors. We consider a context-aware computing environment providing composite and adapted service to users and propose an information processing model that characterizes the device where the collected data should be processed through services and/or applications. Based on this model, we provide an analytical tool to obtain some performance measures of the context-aware computing environment.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1391-1402
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• 2021

This paper focuses use context-sensitive spelling error correction using generative adversarial network. Generative adversarial network[1] are attracting attention as they solve data generation problems that have been a challenge in the field of deep learning. In this paper, sentences are generated using word embedding information and reflected in word distribution representation. We experiment with DCGAN[2] used for the stability of learning in the existing image processing and D2GAN[3] with double discriminator. In this paper, we experimented with how the composition of generative adversarial networks and the change of learning corpus influence the context-sensitive spelling error correction In the experiment, we correction the generated word embedding information and compare the performance with the actual word embedding information.