Show HN: We designed and implemented graph projection feature
38 points| nito98 | 3 years ago
You can now do graph analysis with PageRank, degree centrality, betweenness centrality, or any other algorithm on subgraphs without any additional adjustments. Before you had to create new query procedure. You can fire up a graph machine learning algorithm, such as Temporal graph networks and split the dataset inside the query to do training and validation without splitting the dataset programmatically. And last but not least, you can use your graphics card to run one of cuGraph's algorithms on subgraph in terms of seconds.
You can find the whole explanation in blog post [1] and you can checkout the code at Memgraph GitHub [2]. Furthermore you can check cuGraph's algorithms we have integrated [3]
I'd like to hear your feedback on our approach. Also if you have any general feedback, just write it in the comments :)
[1] https://memgraph.com/blog/how-we-designed-and-implemented-gr...
[2] https://github.com/memgraph/memgraph/
[3] https://memgraph.com/docs/mage/query-modules/cuda/cugraph
Dr_ReD|3 years ago
nito98|3 years ago
Graph represents a data structure which consists of finite set of nodes and edges which are connecting two nodes. Best example to think of graph is social network. There nodes represent people, and edges represent friendships, or follows. For example if I were to follow you and we want to represent it with graph, there would be two nodes (me and you) and edge from me as node to you as node.
Hope it is clear :)
ensignavenger|3 years ago
nito98|3 years ago
nito98|3 years ago
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