• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.51-67
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• 2004

World Wide Web is nearly ubiquitous and the tremendous growing number of Web information strongly requires a structuring framework by which an overview visualization of Web sites has provided as a visual surrogate for the users. We have a viewpoint that the Web site is a directed graph with nodes and arcs where the nodes correspond to Web pages and the arcs correspond to hypertext links between the Web pages. In dealing with the WWW, the goal in this paper is not to derive a naive shortest path or a fast access method, but to generate an optimal structure based on the context centric weight. We modeled a Web site formally so that a integer programming model can be formulated. Even if changes such as modification of the query terms, the optimized Web site structure can be maintained in terms of sensitivity.

• Management Science and Financial Engineering
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• v.9 no.1
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• pp.11-27
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• 2003

In this study, we propose a mathematical model based on the graph theory for the wavelength assignment problem arising in the design of SDH (Synchronous Digital Hierarchy) over WDM (Wavelength Division Multiplexing) ring networks. We propose a branch- and -price algorithm to solve the suggested models effectively within reasonable time in realistic SDH over WDM ring networks. By exploiting the structure of ring networks, we developed a polynomial time algorithm for efficient column generation and a branching rule that conserves the structure of column generation. In a computer simulation study, the suggested approach can find the optimal solutions within reasonable time and show better performance than the existing heuristics.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.4
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• pp.63-82
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• 2008

The explosively growing attractiveness of the Web is commencing significant demands for a structuring analysis on various web objects. The larger the substantial number of web objects are available, the more difficult for the clients(i.e. common web users and web robots) and the servers(i.e. Web search engine) to retrieve what they really want. We have in mind focusing on the structure of web objects by introducing optimization models for more convenient and effective information retrieval. For this purpose, we represent web objects and hyperlinks as a directed graph from which the optimal structures are derived in terms of rooted directed spanning trees and Top-k trees. Computational experiments are executed for synthetic data as well as for real web sites' domains so that the Lagrangian Relaxation approaches have exploited the Top-k trees and Hop constraint resolutions. In the experiments, our methods outperformed the conventional approaches so that the complex web graph can successfully be converted into optimal-structured ones within a reasonable amount of computation time.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.684-690
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• 2007

We describe our method to predict the direction of conditional probabilistic dependencies between clusters of random variables. Selected variables called 'gateway variables' are used to predict the conditional probabilistic dependency relations between clusters. The direction of conditional probabilistic dependencies between clusters are predicted by finding directed acyclic graph (DAG)-shaped dependency structure between the gateway variables. We show that our method shows meaningful prediction results in determining directions of conditional probabilistic dependencies between clusters.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.149-156
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• 2021

Gambling negatively affects the economy, and it brings unwanted financial, social, and health outcomes to gamblers. On the one hand, unemployment is argued to be a leading cause of gambling. On the other hand, gambling can cause unemployment in the second-order via gambling-induced poor health, falling productivity, and crime. In terms of significant effects, previous studies were able to establish an association, but not causality. The current study examines the time-sequence and contemporaneous causalities between lottery gambling and unemployment in Thailand. The Granger causality and directed acyclic graph (DAG) tests employ time-series data on gambling- and unemployment-related Google Trends indexes from January 2004 to April 2021 (208 monthly observations). These tests are based on the estimates from a vector autoregressive (VAR) model. Granger causality is a way to investigate causality between two variables in a time series. However, this approach cannot detect the contemporaneous causality among variables that occurred within the same period. The contemporaneous causal structure of gambling and unemployment was identified via the data-determined DAG approach. The use of time-series Google Trends indexes in gambling studies is new. Based on this data set, unemployment is found to contemporaneously cause gambling, whereas gambling Granger causes unemployment. The causalities are circular and last for four months.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.53-63
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• 2022

In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme "dual-stage Hungarian-based assignment algorithm". Furthermore, we also propose deep learning (DL) based deep neural network (DNN)scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme providessimilar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.

• Journal of the Korea Computer Graphics Society
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• v.8 no.3
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• pp.17-23
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• 2002

Motion capture system is widely used nowadays in the entertainment industry like movies, computer games and broadcasting. This system consist of several high resolution and high speed CCD cameras and expensive frame grabbing hardware for image acquisition. KAIST VR laboratory focused on low cost system for a few years and have been developed a LAN based optical motion capture system. But, by using low cost system some problems like occlusion, noise and swapping of markers' trajectory can be occurred. And more labor intensive work is needed for post-processing process. In this thesis, we propose a trajectory rectification algorithm by confidence model of markers attached on actor. Confidence model is based on graph structure and consist of linkage, marker and frame confidence. To reduce the manual work in post-processing, we have to reconstruct the marker graph by maximizing the frame confidence.

• Journal of the Economic Geographical Society of Korea
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• v.1 no.1
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• pp.137-149
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• 1998

It is likely that the spatial structure of the intraurban accessibility as well as the accessibility value of each of the nodes in the subway network is affected by the addition of new linkages. The changes in the accessibility at individual nodes also affect the accessibility in the surrounding areas at some distances away from the nodes. Graph-theoretic algorithms have been developed as a proper measurement scheme for the nodal accessibility in tracked transport networks such as subway networks. However, the graph-theoretic measurements have limitations to estimate the spatial diffusion effect on the surrounding areas. This study proposes a new model for the spatial diffusion effect estimation of nodal accessibility increment in the subway network toward the surrounding areas. Since the distance decay trend of subway station use reflect the spatial diffusion effect of the accessibility of subway station toward the surrounding area. The model is deduced from the subway station use density function which is formulated by the questionnaire survey data.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.921-928
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• 2004

This paper proposed dynamic adaptive model based on discrete probability distribution function and user profile in web based HyperMedia educational systems. This modelsrepresents application domain to weighted direction graph of dynamic adaptive objects andmodeling user actions using dynamically approach method structured on discrete probability function. Proposed probabilitic analysis can use that presenting potential attribute to useractions that are tracing search actions of user in WebMedia structure. This approach methodscan allocate dynamically appropriate profiles to user.