• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.197-209
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• 2011

The increasing popularity of graph data, such as social and online communities, has initiated a prolific research area in knowledge discovery and data mining. As more real-world graphs are released publicly, there is growing concern about privacy breaching for the entities involved. An adversary may reveal identities of individuals in a published graph, with the topological structure and/or basic graph properties as background knowledge. Many previous studies addressing such attacks as identity disclosure, however, concentrate on preserving privacy in simple graph data only. In this paper, we consider the identity disclosure problem in weighted graphs. The motivation is that, a weighted graph can introduce much more unique information than its simple version, which makes the disclosure easier. We first formalize a general anonymization model to deal with weight-based attacks. Then two concrete attacks are discussed based on weight properties of a graph, including the sum and the set of adjacent weights for each vertex. We also propose a complete solution for the weight anonymization problem to prevent a graph from both attacks. In addition, we also investigate the impact of the proposed methods on community detection, a very popular application in the graph mining field. Our approaches are efficient and practical, and have been validated by extensive experiments on both synthetic and real-world datasets.

• Bulletin of the Korean Mathematical Society
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• v.54 no.3
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• pp.763-787
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• 2017

A graph is called 1-planar if it can be drawn in the Euclidean plane ${\mathbb{R}}^2$ such that each edge is crossed by at most one other edge. The weight of an edge is the sum of degrees of two ends. It is known that every planar graph of minimum degree ${\delta}{\geq}3$ has an edge with weight at most 13. In the present paper, we show the existence of edges with weight at most 25 in 3-connected 1-planar graphs.

• 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.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.77-92
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• 2005

An efficient parallel algorithm is presented to find a maximum weight independent set of a permutation graph which takes O(log n) time using O($n^2$/ log n) processors on an EREW PRAM, provided the graph has at most O(n) maximal independent sets. The best known parallel algorithm takes O($log^2n$) time and O($n^3/log\;n$) processors on a CREW PRAM.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.153-160
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• 2008

This paper shows the maximum data flow utilizing the Weight Bipartite Graph Matching system. The Weight Bipartite Graph Matching system sets the data transmission as edges and guides the maximum data flow on the set server and the client. The proposed Weight Bipartite Graph Matching system implements the multi-user interface video conference system. By sending max data to the server and having the client receive the max data, the non-continuance of the motion image frame, the bottleneck phenomenon, and the broken images are prevented due to the excellent capacity. The experiment shows a two-times better excellency than that of the previous flow control.

• Proceedings of the Korean Institute of Building Construction Conference
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• v.y2004m10
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• pp.59-63
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• 2004

In recent days. it is necessary to find environment-friendly way of diposing industrial waste and reclying system. So this study will analyze the property of Porous concrete improved by concrete waste powder and recycled lightweight aggregate and then suggest the ways of reclying. The method deals with experimenting unit weight of capacity. thermal conductivity, compression and ultrasonic pluse velocity. Considering the relation between ultrasonic pluse velocity and unit weight & thermal conductivity through the graph. the result of relation between ultrasonic pluse velocity and unit weight & thermal conductivity on the graph expessed their high interaction shown as direct proportion on the graph. Recycled Porous concrete merits lightweight and adiabatic. Therefore. we will expect that the current using ALC and Recycled Porous concrete has be similar thermal conductivity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.35-42
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• 2014

This paper suggests a method that obtains the minimum spanning tree (MST) far more easily and rapidly than the present ones. The suggested algorithm, firstly, simplifies a graph by means of reducing the number of edges of the graph. To achieve this, it applies a method of eliminating the maximum weight edge if the valency of vertices of the graph is equal to or more than 3. As a result of this step, we can obtain the reduced edge population. Next, it applies a method in which the maximum weight edge is eliminated within the cycle. On applying the suggested population minimizing and maximum weight edge deletion algorithms to 9 various graphs, as many as the number of cycles of the graph is executed and MST is easily obtained. It turns out to lessen 66% of the number of cycles and obtain the MST in at least 2 and at most 8 cycles by only deleting the maximum weight edges.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.228-233
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• 2005

The protein side-chain packing problem (SCPP) is known to be NP-complete. Various graph theoretic based side-chain packing algorithms have been proposed. However as the size of the protein becomes larger, the sampling space increases exponentially. Hence, one approach to cope with the time complexity is to decompose the graph of the protein into smaller subgraphs. Some existing approaches decompose the graph into biconnected components at an articulation point (resulting in an at-most 21-residue subgraph) or solve the SCPP by tree decomposition (4-, 5-residue subgraph). In this regard, we had also presented a deterministic based approach called as SPWCQ using the notion of maximum edge weight clique in which we reduce SCPP to a graph and then obtain the maximum edge-weight clique of the obtained graph. This algorithm performs well for a protein of less than 500 residues. However, it fails to produce a feasible solution for larger proteins because of the size of the search space. In this paper, we present a new heuristic approach for the side-chain packing problem based on the maximum edge-weight clique finding algorithm that enables us to compute the side-chain packing of much larger proteins. Our new approach can compute side-chain packing of a protein of 874 residues with an RMSD of 1.423${\AA}$.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.25-34
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• 2007

Existing approaches that select an order for the join of three or more data streams have always used the simple heuristics. For their disadvantage - only one factor is considered and that is join selectivity or arrival rate, these methods lead to poor performance and inefficiency In some applications. The graph-based sliding window multi -join algorithm with optimal join sequence is proposed in this paper. In this method, sliding window join graph is set up primarily, in which a vertex represents a join operator and an edge indicates the join relationship among sliding windows, also the vertex weight and the edge weight represent the cost of join and the reciprocity of join operators respectively. Then the optimal join order can be found in the graph by using improved MVP algorithm. The final result can be produced by executing the join plan with the nested loop join procedure, The advantages of our algorithm are proved by the performance comparison with existing join algorithms.

• Korean Journal of Veterinary Service
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• v.24 no.3
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• pp.279-285
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• 2001

The change of the body condition score(BCS) and milk production graph as days in milk by lactation number show that the productivity of cow is on the increase as increase the lactation number, but the health condition is much worse because of the inappropriate nutrition intake. Metabolic profiles test(MPT) results indicate that the early-lactation for directly after the parturition to the peak production of milk during the total lactation period is the time of the more likely to be exposed to lack of energy, protein, minerals. To solve this problem, the early-lactation cows should be sufficiently supplied the required nutrients and should maximum intake the supplied nutrients not to be suddenly decline body weight and BCS from postparturition to the peak production of milk. To maximize the dry matter intake of a cow, there is have got to improve the management of body weight for heifer's skeletal development and in the dry period which is carelessly deal by mostly farms. This study presents that the use of measurement of body weight, graph of body condition score, distribution of milk production, metabolic profiles test in the monitoring for dairy herd health management is very valuable.