Understanding Perception of Small Subgraphs in Graph Theory
Explore the perception of small subgraphs through the study of graph motifs and experimental design, touching on Gestalt principles of similarity and levels of perceptual processing. The research delves into how distinct objects can be grouped together based on similarity, influencing pattern recogn
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Adjacency Labeling Schemes and Induced-Universal Graphs
Adjacency labeling schemes involve assigning L-bit labels to vertices in a graph for efficient edge determination. The concept of induced-universal graphs is explored, where a graph is universal for a family F if all graphs in F are subgraphs of it. Theorems and lower bounds related to adjacency lab
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Efficient Parallel Triangle Listing on Batch-Dynamic Graphs
Efficiently listing triangles in dynamic graphs is essential for identifying dense subgraphs in social networks. This study focuses on fast triangle listing in large graphs, particularly after batch updates, to find new and deleted triangles. The problem statement involves listing all triangles from
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TopK Interesting Subgraph Discovery in Information Networks
Discovering top-K interesting subgraphs in information networks is crucial for various applications like network bottlenecks, team selection, resource allocation, and more. This research focuses on developing low-cost indexes and novel algorithms to efficiently detect these subgraphs. The contributi
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Understanding Topological Sorting in Spark GraphX
Explore the essential concepts of Topological Sorting in Spark GraphX, including necessary background knowledge, stand-alone versus distributed implementations, and practical examples. Delve into Spark GraphX's capabilities, such as RDD manipulation, high-level tools, and graph parallel computation.
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