• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1378-1391
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• 2019

In recent years, automatic document summarization has been widely studied in the field of natural language processing thanks to the remarkable developments made using deep learning models. To decode a word, existing models for abstractive summarization usually represent the context of a document using the weighted hidden states of each input word when they decode it. Because the weights change at each decoding step, these weights reflect only the local context of a document. Therefore, it is difficult to generate a summary that reflects the overall context of a document. To solve this problem, we introduce the notion of a general context and propose a model for summarization based on it. The general context reflects overall context of the document that is independent of each decoding step. Experimental results using the CNN/Daily Mail dataset show that the proposed model outperforms existing models.

• Korean Institute of Interior Design Journal
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• v.19 no.3
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• pp.251-259
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• 2010

The purpose of this study is to show the characteristics of integrated welfare center space by applying Context-Awareness technology in order to provide user-friendly services for efficient use of integrated welfare centers as more and more people are interested in using welfare integrated welfare centers which have increasingly been supplied. For this study, we propose the spaces which provide users of integrated welfare centers with proper services by applying Context-Awareness after reviewing the theory of Context-Awareness through literature study as well as case analysis and choosing the reasonable Context-Awareness technology for integrated welfare centers. As it is possible to efficiently provide users with safety service, information service and convenient service by the analysis of space, users' movement in lobby where Context-Awareness is applied and the lobbies of integrated welfare centers in Munsan area, Paju-si out of domestic cases about integrated welfare centers, the different type of spaces from the existing one is expected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.248-268
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• 2018

The performance of smartphone applications are usually constrained in user interactions due to resource limitation and it promises great opportunities to improve the performance by exploring the smartphone built-in and embedded sensing techniques. However, heterogeneity in techniques, semantic gap between sensor data and usable context, and complexity of contextual situations keep the techniques from seamless integration. Relevant studies mainly focus on feasibility demonstration of emerging sensing techniques, which rarely address both general architectures and comprehensive technical solutions. Based on a proposed functional model, this investigation provides a general architecture to deal with the dynamic context for context-aware automation and decision support. In order to take advantage of the built-in sensors to improve the performance of mobile applications, an ontology-based method is employed for context modelling, linguistic variables are used for heterogeneous context presentation, and semantic distance-based rule matching is employed to customise functions to the contextual situations. A case study on mobile application authentication is conducted with smartphone built-in hardware modules. The results demonstrate the feasibility of the proposed solutions and their effectiveness in improving operational efficiency.

• 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.

• Publications of The Korean Astronomical Society
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• v.7 no.1
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• pp.107-148
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• 1992

This paper presents a cosmological perturbation analysis in a Newtonian framework, using the Newtonian multi component version of the relativistic covariant equations. This work considers the fully nonlinear evolution of the perturbations, and is generalized to multicomponent systems and imperfect fluids. Known nonlinear solutions are presented in a general framework. Quasi-nonlinear analysis, considering both the compressible and rotational modes, is presented, including cases already known in the literature. The Fourier space representation of the conservation equations is also derived in a general context, with various decompositions of the velocity field. Commonly accepted cosmogonical frameworks are critically examined in the context of nonlinear evolution. This work may be regarded as the Newtonian counterpart of a recently presented general relativistic covariant formulation.

• Journal of Korean Elementary Science Education
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• v.32 no.4
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• pp.464-472
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• 2013

The purpose of this study was to analyze the science inquiry problem finding ability of gifted elementary students of science and general elementary students. For this purpose, this study analyzed the types of science inquiry problems in an ill-structured problem finding situation. Also, this study has compared science inquiry problem finding abilities of those two groups. From the results of this study, new ways of improving student' science inquiry problem finding ability and selection of gifted students of science were suggested. The results of this study can be summarized as follows. First, most of the inquiry problems generated by the scientifically gifted and the general students in an ill-structured problem situation could be categorized into seven types (measurement, method, cause, possibility, what, comparison, relationship) according to the inquiry objectives, and both group found more problems in scientific context than in everyday context. Regardless of the context of problem, scientifically gifted students found more problems and the type of problems generated by them were more various than those of general students. Second, there were differences in problem finding ability between scientifically gifted and general students. Scientifically gifted students found more problems and the quality of problems were higher than general students.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.581-588
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• 2014

To facilitate the implementation of a wide variety of context-aware applications based on mobile devices, general-purpose context-aware framework that applications can use by calling is needed. The context-aware framework is a middleware that performs the sensing, reasoning, and retrieving based on the knowledge base. The knowledge base must systematically represent the information required on the behavior of the context-aware framework, such as context information and reasoning information. It must also provide functions for storage and retrieval. To date, previous research on the representation of the context information have been carried out, but studies on the unified representation of the knowledge base has seen little progress. This study defines the knowledge base as the unified context information, and proposes the UniOWL, which can do a good job of representing it. UniOWL is based on OWL and represents the information that is necessary for the operation of the context-aware framework. Therefore, UniOWL greatly facilitates the implementation of the knowledge base on a context-aware framework.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.109-116
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• 2012

Objective: The aim of this study is to present a solution to problems in the services provided by the general hospitals by creating a user-centric environment through analyzing the User Journey Map and the User Context. Background: The rapid growth in aging population and the monopolization of superior medical staffs by the general hospitals increased demand for the general hospitals in Korea. But, often services provided by the general hospitals are provider-centric and low quality. Method: This study examines problems in the services provided by the general hospitals by analyzing the User Journey Map through stakeholder interviews(contextual interviews) and on-site observation. Based on the contextual analysis of the user(i.e. the patient), this study proposes new and improved user-centric services to be provided by the general hospitals. Results: Ten new user-centric services proposed by this study are: (1) "Booklet on Success Story", (2) "FAQs by Doctor", (3) "Designated Nurse", (4) "Patient Interview Record Card", (5) "Close relationship between doctor & patient", (6) "Thank You Notice Board", (7) "Step by Step", (8) "Green Cap", (9) "Patient Kit", (10) "RFID Direction Display System". Conclusion: The service design for the general hospitals proposed by this study is an important case-study on improving the environment of the general hospitals from provider(medical staffs)-centric to user(patents and its family)-centric. Application: This study is expected to be used in various areas to improve existing system(products and/or services) to be more user-centric.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.83-88
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• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• Journal of Information Science Theory and Practice
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• v.10 no.1
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• pp.73-88
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• 2022

This exploratory study aims to understand the potential of log data analysis and expand its utilization in user research methods. Transaction log data are records of electronic interactions that have occurred between users and web services, reflecting information-seeking behavior in the context of digital libraries where users interact with the service system during the search for information. Two ways were used to analyze South Korea's National Digital Science Library (NDSL) log data for three days, including 150,000 data: a log pattern analysis, and log context analysis using statistics. First, a pattern-based analysis examined the general paths of usage by logged and unlogged users. The correlation between paths was analyzed through a χ² analysis. The subsequent log context analysis assessed 30 identified users' data using basic statistics and visualized the individual user information-seeking behavior while accessing NDSL. The visualization shows included 30 diverse paths for 30 cases. Log analysis provided insight into general and individual user information-seeking behavior. The results of log analysis can enhance the understanding of user actions. Therefore, it can be utilized as the basic data to improve the design of services and systems in the digital library to meet users' needs.