• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.437-438
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• 2011

Spectral segmentation is a major trend in image segmentation. Specially, constrained spectral segmentation, inspired by the user-given inputs, remains its challenging task. Since it makes use of the spectrum of the affinity matrix of a given image, its overall quality depends mainly on how to design the graphical model. In this work, we propose a sparse, multi-layer graphical model, where the pixels and the over-segmented regions are the graph nodes. Here, the graph affinities are computed by using the must-link and cannot-link constraints as well as the likelihoods that each node has a specific label. They are then used to simultaneously cluster all pixels and regions into visually coherent groups across all layers in a single multi-layer framework of Normalized Cuts. Although we incorporate only the adjacent connections in the multi-layer graph, the foreground object can be efficiently extracted in the spectral framework. The experimental results demonstrate the relevance of our algorithm as compared to existing popular algorithms.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.109-114
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• 2018

Collaborative filtering has been widely utilized in recommender systems as typical algorithm for outstanding performance. Since it depends on item rating history structurally, The more sparse rating matrix is, the lower its recommendation accuracy is, and sometimes it is totally useless. Variety of hybrid approaches have tried to combine collaborative filtering and content-based method for improving the sparsity issue in rating matrix. In this study, a new method is suggested for the same purpose, but with different perspective, it deals with no-match situation in person-person similarity evaluation. This method is called the transitive similarity model because it is based on relation graph of people, and it compares recommendation accuracy by applying to Movielens open dataset.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.974-983
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• 2005

In genetic algorithms with lotus-based encoding, static gene reordering is to locate the highly related genes closely together. It helps the genetic algorithms to create and preserve the schema of high-quality effectively. In this paper, we propose a static reordering framework for linear locus-based encoding. It differs from existing reorderings in that it is independent of problem-specific knowledge. It makes a complete graph where weights represent the interelationship between each pair of genes. And, it transforms the graph into a unweighted sparse graph by choosing the edges having relatively high weight. It finds a gene reordering by graph search method. Through the wide experiments about several problems, the method proposed in this paper shows significant performance improvement as compared with the genetic algorithm that does not rearrange genes.

• Journal of Korea Water Resources Association
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• v.31 no.4
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• pp.439-448
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• 1998

There are many methods to calculate steady-state flowrate in a large water distribution system. Linear method which analyzes continuity equations and energy equations simultaneously is most widely used. Though it is theoretically simple, when it is applied to a practical water distribution system, it produces a very sparse coefficient matrix and most of its diagonal elements are to be zero. This sparsity characteristic of coefficient matrix makes it difficult to analyze pipe flow using the linear method. In this study, a graph theory is introduced to water distribution system analysis in order to prevent from producing ill-conditioned coefficient matrix and the technique is developed to produce positive-definite matrix. To test applicability of developed method, this method is applied to 22 pipes and 142 pipes system located nearby Taegu city. The results obtained from these applications show that the method can calculate flowrate effectively without failure in converage. Thus it is expected that the method can analyze steady state flowrate and pressure in pipe network systems efficiently. Keywords : pipe flow analysis, graph theory, linear method.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.58-60
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• 2006

대사 경로를 자동으로 레이아웃 해주는 시스템에 있어 노드 수가 일정수 이상으로 증가할수록 에지 크로싱이 기하급수적으로 증가하는 문제가 있다. 따라서 유전체 수준에서 대사 경로간의 관계(Cross-talk) 등을 살펴보기 위해서는 레이아웃 상에 나타나는 에지 크로싱을 줄이고 이를 압축하여 표시할 필요가 있다. 이는 개개의 대사경로에 대한 레이아웃 분만 아니라 대사 경로간의 관계 등 다양한 단계와 방식의 레이아웃이 가능한 시스템이 필요하기 때문이다. 본 논문에서는 레이아웃 상에 나타나는 에지 크로싱에 의한 가독성 저해를 피하기 위하여 대상 경로 상에 존재하는 연결성 높은 부그래프를 찾는 모듈을 개발하였다. 또한 각각의 부그래프를 슈퍼노드로 치환하는 방식을 적용함으로써 대사 경로를 이해하기 쉽도록 하였다. 또한 이러한 과정은 반복적, 혹은 역방향으로 실행할 수 있도록 하였다. 실험결과, 대사 경로 상에 존재하는 연결성 높은 부그래프들은 그래프밀도값 Q가 0.8로 나타나, 단백질 상호작용 네트워크에 비하여 희소한(sparse) 네트워크 구조를 보임을 알 수 있었다.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.681-688
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• 2015

The k nearest neighbor (k-NN) graph construction is an important operation with many web-related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Despite its many elegant properties, the brute force k-NN graph construction method has a computational complexity of $O(n^2)$, which is prohibitive for large scale data sets. Thus, (Key, Value)-based distributed framework, MapReduce, is gaining increasingly widespread use in Locality Sensitive Hashing which is efficient for high-dimension and sparse data. Based on the two-stage strategy, we engage the locality sensitive hashing technique to divide users into small subsets, and then calculate similarity between pairs in the small subsets using a brute force method on MapReduce. Specifically, generating a candidate group stage is important since brute-force calculation is performed in the following step. However, existing methods do not prevent large candidate groups. In this paper, we proposed an efficient algorithm for approximate k-NN graph construction by regrouping candidate groups. Experimental results show that our approach is more effective than existing methods in terms of graph accuracy and scan rate.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.791-796
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• 1987

In this paper, an efficient algorithm to estimate the volume and surface area from ultrasonic imaging and a reconstruction algorithm to generate three-dimensional graphics are presented. The computing efficiency is Improved by using the graph theory and the algorithm to determine proper contour points is performed by applying several tolerances. The search for contour points is limited by the change in curvature in order to provide an efficient search of the minimum cost path. These algorithms are applied to a selected mathematical model of ellipsoid. The results show that the measured value of the volume and surface area for the tolerances of 1.0005, 1.001 and 1.002 approximate to the measured values for the tolerance of 1.000 resulting in small errors. The reconstructed 3-dimensional Images are sparse and consist of larger triangular tiles between two cross sections as tolerance is increased.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.433-435
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• 2007

Geographic wireless sensor networks use position information for Greedy routing. Greedy routing works well in dense network where as in sparse network it may fail and require the use of recovery algorithms. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costlier for resource constrained position based wireless sensor type networks. In the present work, we propose a Void Avoidance Algorithm (VAA); a novel idea based on virtual distance upgrading that allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forward packet using greedy routing only without recovery algorithm. In VAA, the stuck node upgrades distance unless it finds next hop node which is closer to the destination than itself. VAA guarantees the packet delivery if there is a topologically valid path exists. NS-2 is used to evaluate the performance and correctness of VAA and compared the performance with GPSR. Simulation results show that our proposed algorithm achieves higher delivery ratio, lower energy consumption and efficient path.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.5
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• pp.468-574
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• 1991

In construction of breadth-frist tree, the communication complexity can be reduced by efficent synchronization schemes based on several threshold values, We determine several new threshold values by considering the graph density represented as lognm, where n and m are the number of nodes and links., repectively. When thesethreshold values are used in the synchroization method for constructing distrbuted bradth-first search tree, we can obtain a more efficient algorithm in sparse graphs, and also, this algorithm has vthe same performance for communication complexity in dense graphs.