Elastic{Meetup} #20 - Lausanne

Schedule

• 19:00 Welcome, Networking
• 19:25 Intro
• 19:30 Building and deploying Kibana plugins by Alexandre Masselot (https://www.linkedin.com/in/alexmass/)
• 20:00 Multiple ways of building a recommender system with Elasticsearch by Andrii Vozniuk (https://www.linkedin.com/in/vozniuk/)
• 20:30 Networking, Beer, Snacks

Talks

Building and deploying Kibana plugins by Alexandre Masselot (https://www.linkedin.com/in/alexmass/)

The possibility of creating custom plugins is a strong promise of Kibana. We provide an end to end tutorial to write such plugins. But this "end to end" approach also means "how to continuously deploy them?" and "how to share an environment with seeded data?" Those questions will bring us to a full fledged integration infrastructure, backed by Docker. This talk will more or less cover the approach described in one of my recent blog post (http://blog.octo.com/en/a-journey-into-industrializing-the-writing-and-deployment-of-kibana-plugins-riding-docker/)

Multiple ways of building a recommender system with Elasticsearch by Andrii Vozniuk (https://www.linkedin.com/in/vozniuk/)

Elasticsearch (ES) is commonly known as a search and analytics engine. At the same time, information retrieval techniques available in ES can be used to deliver additional value to the users by providing recommendations.
In my talk, I will show how to employ ES to obtain various types of recommendations. We will consider basic content-based techniques as well as hybrid ones involving automatic user interests identification. Considering the example of our web app Graasp (http://graasp.net), I will give ideas how recommendations can be integrated into your product.