Neo4j's Similarity Algorithms and How to Use Them
Details
In this talk we will present similarity algorithms available in neo4j-graph-algorithms (https://neo4j.com/docs/graph-algorithms/current/) library and talk about their use cases. Similarity algorithms do as the name suggests find similar nodes in our graph where the similarity can be defined as euclidean distance between two feature sets or other metrics such as Jaccard index.
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ABOUT THE SPEAKER
Tomaž Bratanič is a freelance developer who helps businesses become data-driven. This includes both defining KPIs and implementing dashboard systems to track them in near real time. He also has a lot of experience working with marketing teams on implementing and tracking of marketing campaigns.
In his free time he contributes to Neo4j graph algorithms library documentation and describes Neo4j and graph algorithm use cases on his blog, which you can find at tbgraph.wordpress.com
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YOUTUBE LIVE LINK:
We'll be hosting this session on YouTube live:
https://www.youtube.com/watch?v=-rM8EHLmsjg
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ONLINE DISCUSSIONS
We'll be taking questions live during the session, but if you have any questions before or after be sure to post them in the project's thread in the Neo4j Community Site (https://community.neo4j.com/t/community-detection-based-on-jaccard-similarity-index-with-neo4j/2249).
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TIME
09:00 PST (UTC - 8 hours)
12:00 EST (UTC - 5 hours)
17:00 UTC
18:00 BST
19:00 CEST (UTC + 2 hours)
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Neo4j's Similarity Algorithms and How to Use Them