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v2.x

Graph Algorithms Visualization

The real application scenarios of large graphs frequently involve graph algorithms. Ultipa Manager encapsulates graph algorithms based on below categories:

  • Similarity: various kinds of similarity calculations such as Jaccard, Cosine, etc.
  • Community detection: such as Louvain community detection, label propagation LPA, belief propagation, etc.
  • Centrality & adjacency: all kinds of ranking algorithm, circle detection, relevance matching, closeness analysis, etc.
  • Degree: all kinds of outDegree/InDegree calculation, etc.
  • Path & flow calculation: calculations of MST (minimum spanning tree), connected sub-graph, path distribution, etc.
  • Graph matching and query
  • Graph embedding and graph convolution: such as Random Walking, node2vec, word2vec, struc2vec, LINE, etc.

Ultipa graph algorithms are coded in compliance with industrial standard and optimized with highly parallel computing; a large number of graph algorithms are completed in real time or near real time. For example, the Louvain community detection algorithm that requires multiple iterations over a full set of data (all nodes and edges) runs hundreds to thousands of times better on Ultipa Server than on other graph databases, graph computing engines, or Python libraries.

Ultipa Manager provides a very friendly user interface for running graph algorithms. Users can select the algorithm from Algo dashboard and enter value of the required parameters for calculation; no need to manually enter the uQL command in the CLI.

Under Algo module in the sidebar, algoritms are displayed in two styles, the default widget style:

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