• The Korean Journal of Archival Studies
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• no.32
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• pp.3-44
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• 2012

The purpose of the study is to explore the strategies to build participatory digital archives for documenting localities. Following the introduction of the chapter one, the chapter two deals with categorizing participation types of persons and organizations for documenting localities, analysing characteristics and benefits of each type, and listing up the requirements of participatory archives based on literature reviews. The chapter three focuses on the analyses of digital archives especially based on the participation of organizations such as collecting institutions and community archives in USA, Canada and UK. The cases of participatory archives are divided into two types; i) digital archives based on archival collections of institutions such as libraries, archives, and museums, ii) digital archives mainly based on various community archives. Online Archives California(OAC) and Calisphere of University of California, MemoryBC of British Columbia of Canada, and People's Collection Wales of UK as the first type cases, and Connecting Histories of Birmingham, 'Community Archives Wales(CAW), Cambridgeshire Community Archive Network(CCAN), Norfolk Community Archives Network(NORCAN) as the second type cases are selected for comparative analyses. All these cases can be considered as archival portals since they cover collections from various organizations. This study then evaluates how these digital archives fulfill the requirements of participatory archives such as : i) integrated search of archives that are to be distributed, ii) participation of individuals and organizations, and iii) providing broader contextual information and representation of context as well as contents of archives. Lastly the final chapter suggests the implications for building participatory archives in Korean local areas based on following aspects : host organizations and implementation strategy, networks of collection institutions and community archives, preserving and reorganizing contextual information, selection and appraisal, and participation of records users and creators.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.83-102
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• 2008

Ubiquitous computing requires timely supply of contextual information in order to upgrade decision quality. In this sense, this study is aimed at proposing a multi-dynamic decision support system for highly ill-structured problems. Especially, it is very important for decision makers in the ubiquitous computing to coordinate conflicts among local goals and global goal harmoniously. The proposed Multi-Dynamic Decision Support System (MDDSS) is basically composed of both central structure and distributed structure, in which central structure supports multi objects decision making and distributed structure supports individual decision making. Its hybrid architecture consists of decision processor, multi-agent controller and intelligent knowledge management processor. Decision processor provides decision support using contexts which come from individual agents. Multi-agent controller coordinates tension among multi agents to resolve conflicts among them. Meanwhile, intelligent knowledge management processor manages knowledge to support decision making such as rules, knowledge, cases and so on. To prove the validity of the proposed MDDSS, we applied it to an u-fulfillment problem system in which many kinds of decision makers exist trying to satisfy their own objectives, and timely adjustment of action strategy is required. Therefore, the u-fulfillment problem is a highly ill-structured problem. We proved its effectiveness with the aid of multi-agent simulation comprising 60 customers and 10 vehicles under three experimental modes.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.691-701
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• 2013

In this paper, an early termination algorithm for merge process is proposed to reduce the computational complexity in High Efficiency Video Coding (HEVC) encoder. In the HEVC, the same candidate modes from merge candidate list (MCL) are shared to predict a merge or merge SKIP mode. This search process is performed by the number of the obtained candidates for the both of the merge and SKIP modes. This may cause some redundant search operations. To reduce this redundant search operation, we employ the neighboring blocks which have been encoded in prior, to check on the contextual information. In this study, the spatial, temporal and depth neighboring blocks have been considered to compute a correlation information. With this correlation information, an early termination algorithm for merge process is suggested. When all modes of neighboring blocks are SKIP modes, then the merge process performs only SKIP mode. Otherwise, usual merge process of HEVC is performed Through experimental results, the proposed method achieves a time-saving factor of about 21.25% on average with small loss of BD-rate, when comparing to the original HM 10.0 encoder.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.193-205
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• 2021

The AI speaker market is growing steadily. However, the satisfaction of actual users is only 42%. Therefore, in this paper, we collected reviews on Amazon Echo Dot 3rd and 4th generation models to analyze what hinders the user experience through the topic changes and emotional changes of each generation of AI speakers. By using topic modeling analysis techniques, we found changes in topics and topics that make up reviews for each generation, and examined how user sentiment on topics changed according to generation through deep learning-based sentiment analysis. As a result of topic modeling, five topics were derived for each generation. In the case of the 3rd generation, the topic representing general features of the speaker acted as a positive factor for the product, while user convenience features acted as negative factor. Conversely, in the 4^th generation, general features were negatively, and convenience features were positively derived. This analysis is significant in that it can present analysis results that take into account not only lexical features but also contextual features of the entire sentence in terms of methodology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.2
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• pp.125-137
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• 2007

This paper proposes a new scheme to provide the location privacy of sources in Wireless Sensor Networks (WSNs). Because the geographical location of a source sensor reveals contextual information on an 'event' in WSN, anonymizing the source location is an important issue. Despite abundant research efforts, however, about data confidentiality and authentication in WSN, privacy issues have not been researched well so far. Moreover, many schemes providing the anonymity of communication parties in Internet and Ad-hoc networks are not appropriate for WSN environments where sensors are very resource limited and messages are forwarded in a hop-by-hop manner through wireless channel. In this paper, we first categorize the type of eavesdroppers for WSN as Global Eavesdropper and Compromising Eavesdropper. Then we propose a novel scheme which provides the anonymity of a source according to the types of eavesdroppers. Furthermore, we analyze the degree of anonymity of WSN using the entropy-based modeling method. As a result, we show that the proposed scheme improves the degree of anonymity compared to a method without any provision of anonymity and also show that the transmission range plays a key role to hide the location of source sensors.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.229-247
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• 2023

With the increasing emphasis on anomaly detection across various fields, diverse anomaly detection algorithms have been developed for various data types and anomaly patterns. However, the performance of anomaly detection algorithms is generally evaluated on publicly available datasets, and the specific performance of each algorithm on anomalies of particular types remains unexplored. Consequently, selecting an appropriate anomaly detection algorithm for specific analytical contexts poses challenges. Therefore, in this paper, we aim to investigate the types of anomalies and various attributes of data. Subsequently, we intend to propose approaches that can assist in the selection of appropriate anomaly detection algorithms based on this understanding. Specifically, this study compares the performance of anomaly detection algorithms for four types of anomalies: local, global, contextual, and clustered anomalies. Through further analysis, the impact of label availability, data quantity, and dimensionality on algorithm performance is examined. Experimental results demonstrate that the most effective algorithm varies depending on the type of anomaly, and certain algorithms exhibit stable performance even in the absence of anomaly-specific information. Furthermore, in some types of anomalies, the performance of unsupervised anomaly detection algorithms was observed to be lower than that of supervised and semi-supervised learning algorithms. Lastly, we found that the performance of most algorithms is more strongly influenced by the type of anomalies when the data quantity is relatively scarce or abundant. Additionally, in cases of higher dimensionality, it was noted that excellent performance was exhibited in detecting local and global anomalies, while lower performance was observed for clustered anomaly types.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Korean journal of communication and information
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• v.41
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• pp.200-231
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• 2008

This study content-analyzed Korean cable television programs aired from Feb. 6 to Feb. 19, 2007, focusing on the contextual variables linked to violent acts. A total of 657 PAT's (perpetrator-action-target) in the 68 programs sampled were analyzed for characters' age, sex, type, relationship, and motivation, humorization, punishment for their violent acts, and finally reality of violence. According to the results, (1) most violence occurred among male characters, who were at their ages between 20 and 39; (2) more than half of the total violent acts happened among acquaintances including family members; (3) anger, retaliation, personal or group interest, and violence for fun were ranked at the top tiers of the motivation list; (4) most violences were overlooked without punishment; (5) and about 80% of the whole violence were realistic. In terms of program types, (1) female perpetrator and victims appealed more often in drama than the other genres; (2) violence among acquaintances and simple fun as motivation were prevalent most in entertainment programs; (3) every violent act in children's programs was done by unrealistic characters. According to the analysis by program ratings, (1) while least violence appeared in '19 and older', all of the violent acts were portrayed as realistic; (2) humorization were most prevalent in the 'everyone' rating; (3) and female perpetrators and victims appealed most in the programs rated as '15 and older'. Generally, various contextualized violences displayed different distributions according to program types and ratings. The qualitative features of the current findings about cable television violence provide a fundamental data for future studies, which will explore the subsequent effects of violent media contents.

• Korean journal of communication and information
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• v.62
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• pp.179-199
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• 2013

This study is aimed to draw the meaning and possibility of political participation of the SNS users through a phenomenological analysis of participation and awareness of authentication shot for vote of the users. Especially, the reason for focusing on 'SNS vote authentication shot' is because the creative imagination of the users and the meaning and possibility of collective intelligence are drew while citizens are participating in political activities for themselves. Theory resources are based on technical imagination of Vil$\acute{e}$m Flusser that is concerned with users and political practice in the New Media Era, creative imaginer and discussions of collective intelligence of Pierre L$\acute{e}$vy. Based on these theoretical discussions, it is aimed to select the SNS users experienced in authentication shot for the by-election for mayor of Seoul in 26. Oct. 2011 and to use phenomenological analysis model on materials collected after in-depth interview. The researchers take contextual circumstance into consideration for experiences of study participants sticking to SNS users' opinions and intersubjectivity and approach prejudice of their experiences to untouched structure of phenomenon and meaning. It is because a phenomenological study exploring "the own meaning of 'die Sachen'" is 'strict study' and method focusing on the political participation of SNS users itself.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.99-120
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• 2017

In order to develop a semiautomatic support system that allows researchers concerned to efficiently analyze the technical trends for the ever-growing industry and market. This paper introduces a couple of Korean sentence generation models that can automatically generate definitional statements as well as descriptions of technical terms and concepts. The proposed models are based on a deep learning model called LSTM (Long Sort-Term Memory) capable of effectively labeling textual sequences by taking into account the contextual relations of each item in the sequences. Our models take technical terms as inputs and can generate a broad range of heterogeneous textual descriptions that explain the concept of the terms. In the experiments using large-scale training collections, we confirmed that more accurate and reasonable sentences can be generated by CHAR-CNN-LSTM model that is a word-based LSTM exploiting character embeddings based on convolutional neural networks (CNN). The results of this study can be a force for developing an extension model that can generate a set of sentences covering the same subjects, and furthermore, we can implement an artificial intelligence model that automatically creates technical literature.