• Journal of KIISE
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• v.42 no.8
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• pp.998-1009
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• 2015

In recent years, there has been a growing interest in RDFS Inference to build a rich knowledge base. However, it is difficult to improve the inference performance with large data by using a single machine. Therefore, researchers are investigating the development of a RDFS inference engine for a distributed computing environment. However, the existing inference engines cannot process data in real-time, are difficult to implement, and are vulnerable to repetitive tasks. In order to overcome these problems, we propose a method to construct an in-memory distributed inference engine that uses a parallel graph structure. In general, the ontology based on a triple structure possesses a graph structure. Thus, it is intuitive to design a graph structure-based inference engine. Moreover, the RDFS inference rule can be implemented by utilizing the operator of the graph structure, and we can thus design the inference engine according to the graph structure, and not the structure of the data table. In this study, we evaluate the proposed inference engine by using the LUBM1000 and LUBM3000 data to test the speed of the inference. The results of our experiment indicate that the proposed in-memory distributed inference engine achieved a performance of about 10 times faster than an in-storage inference engine.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1407-1423
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• 2020

A graph is a data structure consisting of nodes and edges between these nodes. Graph embedding is to generate a low dimensional vector for a given graph that best represents the characteristics of the graph. Recently, there have been studies on graph embedding, especially using deep learning techniques. However, until now, most deep learning-based graph embedding techniques have focused on unweighted graphs. Therefore, in this paper, we propose a graph embedding technique for weighted graphs based on long short-term memory (LSTM) autoencoders. Given weighted graphs, we traverse each graph to extract node-weight sequences from the graph. Each node-weight sequence represents a path in the graph consisting of nodes and the weights between these nodes. We then train an LSTM autoencoder on the extracted node-weight sequences and encode each nodeweight sequence into a fixed-length vector using the trained LSTM autoencoder. Finally, for each graph, we collect the encoding vectors obtained from the graph and combine them to generate the final embedding vector for the graph. These embedding vectors can be used to classify weighted graphs or to search for similar weighted graphs. The experiments on synthetic and real datasets show that the proposed method is effective in measuring the similarity between weighted graphs.

• The Pure and Applied Mathematics
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• v.19 no.4
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• pp.349-361
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• 2012

CAT(0) cubical complexes are a key to formulate geodesic spaces with nonpositive curvatures. The paper discusses the median structure of CAT90) cubical complexes. Especially, the underlying graph of a CAT(0) cubical complex is a median graph. Using the idea of median structure, this paper shows that groups acting on median complexes L(${\delta}$) groups and, in addition, work L(0) groups are closed under free product.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.623-626
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• 2000

The purpose of this paper is to find an efficient solution for multiple constant multiplication (MCM) problem. Since the circuit structure can be represented as a directed acyclic graph, evolutionary computing is considered as an effective tool for optimization of circuit synthesis. In this paper, we propose a stack type operator as a chromosome element to synthesize a directed acyclic graph efficiently. This type of chromosome can represent a graph structure with a set of simple symbols and so we can employ the similar method to a conventional GA.

• Korean Institute of Interior Design Journal
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• v.18 no.4
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• pp.97-104
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• 2009

This thesis analyzed arrangement and mixture method of function elements, which are getting more important in museum planning. It used quantitative method, Space Syntax and Visibility Graph Analysis tool to analyze five case museums. Through this analysis, advantages and disadvantages of two methods were derived and case museums' arrangement and mixture attributes were grasped. Results of the analysis were derived differently by two kinds of plan form which were room to room type and open type. Open typed museum recorded similar graphs of Integration, Visual Integration and Visual Connectivity. Since whole space structures were relatively simple and structure of exhibition halls were opened, the results of Space Syntax and Visibility Graph Analysis had similar graphs. Room to room typed museum showed differences in Integration, Visual Integration and Visual Connectivity. In the result, the most accessible space was lobby and Mediation Space became the center of visibility. Also, the exhibition hall, where the opening of room to room typed exhibition hall was penetrated visually, became a center of visibility. Lobby space, which was close to entrance, had the highest Visibility Connectivity. As Space Syntax could analyze the museum as whole space structure, Space Syntax showed strength in room to room typed museum analysis compared to open typed museum analysis which has relatively simple structure. Visibility Graph Analysis could expect the flow of exhibit distance including visibility analysis unlike the flow of exhibit distance with space arrangement. The exhibition hall, which secures the sight to penetration of an opening, couldn't be analyzed in existing Space Syntax. However, it became the biggest advantages in Visibility Graph Analysis of room to room typed museum. Visibility Graph Analysis derived detailed results in exhibit arrangement so it will be the useful method not only for architecture but also for planning of exhibit arrangement in open typed museum. Through this study, various possibilities on Quantitative Analysis Method of Museum Architecture could be verified. However, the analysis still has limitation of second dimension. Therefore, diverse and liberal following study will be expected to accomplish.

• East Asian mathematical journal
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• v.21 no.2
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• pp.249-260
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• 2005

Experimentation using computer plays an important part in education and research in graph theory. The purpose of this paper is to develop the CAS techniques for the hands-on approach in graph theory specifically on the topic of constructing the spanning tree. This paper discusses the advantages of CAS as the software system for doing graph theory and introduces the software solutions integrating multimedia user interface developed by the author, which extend the functionality of the existing CAS-based graph theory software package.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.235-242
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• 1997

We characterize the tight structure of a vertex-accumula-tion-free maximal planar graph with no separating triangles. Together with the result of Halin who gave an equivalent form for such graphs this yields that a tight structure always exists in every 4-connected maximal planar graph with one end.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.105-115
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• 2003

An infinite locally finite plane graph is called an LV-graph if it is 3-connected and VAP-free. If an LV-graph G contains no unbounded faces, then we say that G is a 3LV-graph. In this paper, a structure theorem for an LV-graph concerning the existence of a sequence of systems of paths exhausting the whole graph is presented. Combining this theorem with the early result of the author, we obtain a necessary and sufficient conditions for an infinite VAP-free planar graph to be a 3LV-graph as well as an LV-graph. These theorems generalize the characterization theorem of Thomassen for infinite triangulations.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.247-257
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• 2013

A narrative structure is essential for a story generator to create a story plot. In digital storytelling system, a narrative structure can be generally designed as a tree or a graph, and the story generator in the digital storytelling system creates continuous story plots based on the narrative structure. When a narrative structure is designed with a tree or a graph, it is hard for the story generator to create various kinds of story-plots due to the inflexible nature of a tree or graph structure. It may result in degrading the quality of story-plots to provide similar story-plot to various kind of user. In this paper, we proposed an approach to create a story-plot based on association analysis of data mining to overcome the disadvantage. In detail, we defined a narrative structure which consists of narrative patterns, and then implemented a story generator which creates a story-plot using the proposed narrative structure. As a result, we confirmed that implemented story generator was able to create a story-plot according to understanding level of user in case study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1748-1759
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• 2018

Weber Local Descriptor (WLD) is a stable and effective feature extraction algorithm, which is based on Weber's Law. It calculates the differential excitation information and direction information, and then integrates them to get the feature information of the image. However, WLD only considers the center pixel and its contrast with its surrounding pixels when calculating the differential excitation information. As a result, the illumination variation is relatively sensitive, and the selection of the neighbor area is rather small. This may make the whole information is divided into small pieces, thus, it is difficult to be recognized. In order to overcome this problem, this paper proposes Weber Symmetrical Local Graph Structure (WSLGS), which constructs the graph structure based on the $5{\times}5$ neighborhood. Then the information obtained is regarded as the differential excitation information. Finally, we demonstrate the effectiveness of our proposed method on the database of ORL, JAFFE and our own built database, high-definition infrared faces. The experimental results show that WSLGS provides higher recognition rate and shorter image processing time compared with traditional algorithms.