• 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 Korea Information Processing Society Conference
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• 2018.10a
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• pp.984-987
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• 2018

In an Internet of Thing (IoT) environment, entities with different attributes and capacities are going to be connected in a highly connected fashion. Specifically, not only the mechanical and electronic devices but also other entities such as people, locations and applications are connected to each other. Understanding and managing these connections play an important role for businesses, which identify opportunities for new IoT services. Traditional approach for storing and querying IoT data is used of a relational database management system (RDMS) such as MySQL or MSSQL. However, using RDMS is not flexible and sufficient for handling heterogeneous IoT data because these data have deeply complex relationships which require nested queries and complex joins on multiple tables. In this paper, we propose a graph model for constructing a graph database of heterogeneous IoT data. Graph databases are purposely-built to store highly connected data with nodes representing entities and edges representing the relationships between these entities. Our model fuses social graph, spatial graph, and things graph, and incorporates the relationships among them. We then present a case study which applies our model for representing data from a Smart Campus using Neo4J platform. Through the results of querying to answer real questions in Smart Campus management, we show the viability of our model.

• Journal of Contemporary Eastern Asia
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• v.14 no.2
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• pp.87-96
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• 2015

Social media comprises a vast and consequential landscape that has been poorly mapped and understood. Hundreds of millions of people have eagerly moved many of the conversations and discussions that compose civil society into these services and platforms. There is a need to document and analyze these social spaces for many academic and commercial purposes. The Social Media Research Foundation has engaged a strategy to cultivate better research into the structure and dynamics of social media. The foundation is dedicated to the creation of open tools, open data, and open scholarship related to social media. It has implemented a free and open network collection, analysis, and visualization tool called NodeXL to facilitate social media network research. Using NodeXL a group of researchers has collectively authored a publicly available archive, called the NodeXL Graph Gallery, composed of network data sets and visualizations from users around the world. This site has enabled the aggregation of tens of thousands of network datasets and images. Use of the archive has led to scholarly research results that are based on the wide range and scope of social media data sets available.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.5
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• pp.177-188
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• 2018

The scale of graph data has been increased rapidly because of the growth of mobile Internet applications and the proliferation of social network services. This brings upon the imminent necessity of efficient distributed and parallel graph processing approach since the size of these large-scale graphs are easily over a capacity of a single machine. Currently, there are two popular parallel graph processing approaches, vertex-centric graph processing and block centric processing. While a vertex-centric graph processing approach can easily be applied to the parallel processing system, a block-centric graph processing approach is proposed to compensate the drawbacks of the vertex-centric approach. In these systems, the initial quality of graph partition affects to the overall performance significantly. However, it is a very difficult problem to divide the graph into optimal states at the initial phase. Thus, several dynamic load balancing techniques have been studied that suggest the progressive partitioning during the graph processing time. In this paper, we present a load balancing algorithms for the block-centric graph processing approach where most of dynamic load balancing techniques are focused on vertex-centric systems. Our proposed algorithm focus on an improvement of the graph partition quality by dynamically reassigning blocks in runtime, and suggests block split strategy for escaping local optimum solution.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.43-57
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• 2023

Government codes are created and utilized to streamline and standardize government administrative procedures. They are generally employed in government information systems. Because they are included in open datasets of public data, users must be able to understand them. However, information that can be used to comprehend administrative code is lost during the process of releasing data in the government system, making it difficult for data consumers to grasp the code and limiting the connection or convergence of different datasets that use the same code.This study proposes a way to employ the administrative code produced by the Korean government as a standard in a public data environment on a regular basis. Because consumers of public data are barred from accessing government systems, a means of universal access to administrative code is required. An ontology model is used to represent the administrative code's data structure and meaning, and the full administrative code is built as a knowledge graph. The knowledge graph thus created is used to assess the accuracy and connection of administrative codes in public data. The method proposed in this study has the potential to increase the quality of coded information in public data as well as data connectivity.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.42-53
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• 2020

With the development of social network services, graph structures have been utilized to represent relationships among objects in various applications. Recently, a demand of subgraph matching in real-time graph streams has been increased. Therefore, an efficient approximate Top-k subgraph matching scheme for low latency in real-time graph streams is required. In this paper, we propose an approximate Top-k subgraph matching scheme considering data reuse in graph stream environments. The proposed scheme utilizes the distributed stream processing platform, called Storm to handle a large amount of stream data. We also utilize an existing data reuse scheme to decrease stream processing costs. We propose a distance based summary indexing technique to generate Top-k subgraph matching results. The proposed summary indexing technique costs very low since it only stores distances among vertices that are selected in advance. Finally, we provide k subgraph matching results to users by performing an approximate Top-k matching on the summary indexing. In order to show the superiority of the proposed scheme, we conduct various performance evaluations in diverse real world datasets.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.9-19
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• 2013

In this paper, we develop a Spatio-Temporal graph as of a key component of our knowledge representation Scheme. We design an integrated representation scheme to depict not only present and past but future in parallel with the spaces in an effective and intuitive manner. An event in general occupies not only a space but a time. Hence a crucial premise for the simulation of virtual situations is to position events in the multi-dimensional context, that is, 3-D space extended by the temporal dimension. Furthermore an event tends to have physical, social and mental aspects intertwined. As a result we need diverse information structures and functions to model entities and relations associated with events and to describe situations in different stances or perspectives of the virtual agents. These structures and functions are implemented in terms of integrated and intuitive representation schemes at different levels such as Ontology View, Instance View, ST View, Reality View. The resulting multi-dimensional comprehensive knowledge structure accommodates multi-layered virtual world developing in the time to maximize the diversity of situations in the historical context. The viability of this knowledge representation scheme is demonstrated with a typical scenario applied to a simulator implemented based on the ST Graph. The virtual stage based on the ST graph can be used to provide natural contexts for situated learning or next-generation simulation games.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.205-214
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• 2016

As a large amount of graph-structured data is widely used in various applications such as social networks, semantic web, and bio-informatics, keyword-based search over graph data has been getting a lot of attention. In this paper, we propose an efficient method for keyword search over graph data to find a set of top-k answers that are relevant as well as non-redundant in structure. We define a non-redundant answer structure for a keyword query and a relevance measure for the answer. We suggest a new indexing scheme on the relevant paths between nodes and keyword terms in the graph, and also propose a query processing algorithm to find top-k non-redundant answers efficiently by exploiting the pre-calculated indexes. We present effectiveness and efficiency of the proposed approach compared to the previous method by conducting an experiment using a real dataset.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.465-475
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• 2018

Recently, as the use of social media and IoT has increased, large graph streams has been generating and studies on real-time processing for them have been actively carrying out. In this paper we propose a incremental graph stream processing scheme that reuses previous result data when the graph changes continuously. We also propose a cost model to selectively perform incremental processing and static processing. The proposed cost model computes the predicted value of the detection cost and the processing cost of the recalculation area based on the actually processed history and performs the incremental processing when the incremental processing is more profit than the static processing. The proposed incremental processing increases the efficiency by processing only the part that changes when the graph update occurs. Also, by collecting only the previous result data of the changed part and performing the incremental processing, the disk I/O costs are reduced. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• Journal of Information Technology Applications and Management
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• v.18 no.1
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• pp.41-53
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• 2011

The rapid development and widespread application of Internet has provided a platform for people to participate and discuss social hotspot events. In the meantime, social events may be spread throughout the Internet more quickly and widely than they did ever before, and possibly lead to serious social problems due to opinion violence or seditious rumour. This paper analyzed the Internet spread of social events, and presented a five-stage model to describe the evolution process of that spread. Furthermore, the improved IBF algorithm was applied to extract a pruned connected graph aiming to find the key nodes and the shortest spread path for the control of that spread. After analyzing the different factors that may cause the netizens' attention, this paper concluded BBS type, the visit quantity and the opinion leader are key factors which affect the Internet spread. Based on those researches, a life-cycle emergency management methodology and the related strategies were proposed for the achievement of healthy spreading environment on Internet.