• ETRI Journal
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• v.38 no.4
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.55.5-55
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• 2001

The MST (Minimum Spanning Tree) matching algorithm had been used for searching the part accord points extracted from the gray level fingerprint image. The method, however, had some limitations. To obtain the relationship between enrolled and inputted fingerprint, the MST was used to generate the tree graph that represent the unique graph for given fingerprint data. From the graph, the accord points are estimated. However, the shape of the graph highly depends on the positions of the minutiae. If there are some pseudo minutiae caused by noise, the shape of the graph will be different In this paper, to overcome the limitations of the MST, we proposed CRM (Center of Rotation Method) algorithm that found the true part accord points. The proposed method is based on the assumption ...

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.4
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• pp.441-450
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• 2015

The tactical communications network has to be deployed rapidly at military operation area and support the communications between the military command systems and the weapon systems. For that, the frequency assignment is required for backbone wireless links of tactical communications network without frequency interferences. In this paper, we propose a frequency assignment method using net filter discrimination (NFD) and graph coloring to avoid frequency interferences. The proposed method presents frequency assignment problem of tactical communications network as vertex graph coloring problem of a weighted graph. And it makes frequency assignment sequences and assigns center frequencies to communication links according to the priority of communication links and graph coloring. The evaluation shows that this method can assign center frequencies to backbone communication links without frequency interferences. It also shows that the method can improve the frequency utilization in comparison with HTZ-warfare that is currently used by Korean Army.

• Journal of applied mathematics & informatics
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• v.41 no.2
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• pp.287-293
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• 2023

In this paper, the Augmented graph Es(τ) of the inverse graph Gs(τ) of a cyclic group (τ,◦) was studied. The Augmented inverse graph was constructed by applying the method of Mycielski's construction. The dimension of Augmented inverse graph and different properties of the graph were investigated. Later the chromatic number of Augmented inverse graph was discussed and the relation between the maximum degree of the graph and the chromatic number was established. In the Mycielski's construction, the properties of the key node 'u' in Es (τ) were established based on cardinality of the cyclic group (τ,◦) and also proved that the Augmented inverse graph Es(τ) was a triangle free graph.

• 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.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.251-258
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• 2009

Data mining is a method that extract useful knowledges from huge size of data. Recently, a focussing research part of data mining is to find interesting patterns in graph databases. More efficient methods have been proposed in graph mining. However, graph analysis methods are in NP-hard problem. Graph pattern mining based on pattern growth method is to find complete set of patterns satisfying certain property through extending graph pattern edge by edge with avoiding generation of duplicated patterns. This paper suggests an efficient approach of reducing computing time of pattern growth method through pattern growth's property that similar patterns cause similar tasks. we suggest pruning methods which reduce search space. Based on extensive performance study, we discuss the results and the future works.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.10-17
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• 1993

This paper analyzes succinct graph descriptions and its complexity of connectivity problems on context free graph languages under various restrictions. It defines SNLC(Simple Context Free Node Label Controlled) grammar and presents reduction method that solves graph problems without expanding the hierarchical description. It exemplifies the method by giving efficient solutions to connectivity problems on graphs and presents parallel algorithm for reduction and analyzes the complexity. Its results will help application of desing for NETWORK. CAD. VLSI and other engineering problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.718-721
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• 2004

This paper introduces a novel method of partitioning a cyclic workflow graph into the subgraphs of acyclic flows. The way of iterative classification of nodes according to feedback structures and deriving subgraphs of acyclic flows is described with illustrative examples. The proposed method allows a cyclic workflow model to be analyzed further, if necessary, with several smaller subflows, which are all acyclic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4126-4142
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• 2015

Finger vein recognition is a biometric technology using finger veins to authenticate a person, and due to its high degree of uniqueness, liveness, and safety, it is widely used. The traditional Symmetric Local Graph Structure (SLGS) method only considers the relationship between the image pixels as a dominating set, and uses the relevant theories to tap image features. In order to better extract finger vein features, taking into account location information and direction information between the pixels of the image, this paper presents a novel finger vein feature extraction method, Multi-Orientation Weighted Symmetric Local Graph Structure (MOW-SLGS), which assigns weight to each edge according to the positional relationship between the edge and the target pixel. In addition, we use the Extreme Learning Machine (ELM) classifier to train and classify the vein feature extracted by the MOW-SLGS method. Experiments show that the proposed method has better performance than traditional methods.