Name: Knowledge Graph & Observability with ECS - Elastic{Meetup} #47 - Lausanne
Start: 2019-10-22T19:00:00+02:00
End: 2019-10-22T21:00:00+02:00
Location: Liip SA

This meetup will be hosted by our good friends at Liip (https://www.liip.ch).

# Schedule

• 18:30 Welcome, Networking
• 18:55 Intro
• 19:00 Knowledge Graph Embeddings and ES for large-scale content-based Recommender Systems by Mohameth François Sy
• 19:30 Why Observability loves the Elastic Common Schema by Nicolas Ruflin
• 20:00 Networking, Beer, Snacks

# Talks

## Knowledge Graph Embeddings and ElasticSearch for large-scale content-based Recommender Systems by Mohameth François Sy (EPFL - Blue Brain Project)

Knowledge graphs (KGs) have become ubiquitous, created and used by many organisations (from enterprises, research institutions to crowd-sourced open communities) as backbone and driver of many of their intelligent products and applications.

Many KGs such as DBpedia, Microsoft Graph, Google Knowledge Graph, Facebook Social Graph (to name few) have been created to enable and support real world use cases and downstream tasks such as recommendations systems included content-based ones. Leveraging Knowledge graph content, structure and semantics to build an entity recommender system is challenging because of the graph complexity, its high-dimensional and symbolic nature.
However, recent Knowledge graph embeddings approaches have been developed to address the aforementioned challenges. The key idea here is to project KGs entities and relations into low-dimensional vector spaces simpler to deal with and compute from while preserving (as much as possible) the knowledge graph semantics, structure and entity relative similarities. Equipped with such embeddings, knowledge graph can be projected and deployed into ElasticSearch to build large-scale content-based recommender system.

In this talk, I will give an introduction to Knowledge graph through real world examples, expose the challenges they raise, present different Knowledge graph embeddings techniques and demonstrate how to build, deploy and use them in ElasticSearch for entity content-based entity recommendation and similarity computation.

Links:
https://www.epfl.ch/research/domains/bluebrain/blue-brain/people/section-managers-group-leaders/mohameth-francois-sy/
https://www.linkedin.com/in/mofsy/

## Why Observability loves the Elastic Common Schema by Nicolas Ruflin (Elastic)

With the Elastic Stack 7.0 release, the Elastic Common Schema (ECS) was released and adopted. This talk will cover in more detail why ECS was created, what ECS contains and what affect in can have on the observability of your system.

We hope to see you there!

Nicolas Ruflin

Valentin Crettaz

Elastic Switzerland

Elastic

Technology

Machine Learning

Text Analytics

Predictive Analytics

New Technology

SEO (Search Engine Optimization)

Distributed Systems

Big Data

Elasticsearch

Knowledge Graph & Observability with ECS - Elastic{Meetup} #47 - Lausanne

Liip SA

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Knowledge Graph & Observability with ECS - Elastic{Meetup} #47 - Lausanne

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