See:
- http://en.wikipedia.org/wiki/Adaptation_(computer_science)
- https://en.wikipedia.org/wiki/Machine_learning
This will open up tons of use cases for Tiki. Working scenario is that we add Rubix ML, mostly focusing on Trackers
- http://mloss.org/ (machine learning open source software)
- Improve search results with click popularity (learning search)
- 20 lines of code that will beat A/B testing every time
- https://blog.builtwith.com/2013/07/19/whats-happening-in-the-ab-testing-market/
- https://m.facebook.com/notes/facebook-data-science/big-experiments-big-datas-friend-for-making-decisions/10152160441298859
- https://predictionio.apache.org/
- Matomo: A/B testing, Split tests
- https://github.com/innocraft/php-experiments/blob/master/README.md
- https://github.com/Yelp/elastalert
- https://maif.github.io/izanami/
Related: Connect (where we'll aggregate data on mother.tiki.org to make even better adaptations)
Source: http://www.theregister.co.uk/2014/12/23/elasticsearch_big_data_search_tool_fancy_an_elk_hunt/?page=2
https://packagist.org/packages/vimeo/ablincoln
Websites about Machine Learning which are powered by Tiki
These a good people to get in touch with when we start work on this