MARk

The Multi-Agent Ranking framework (MARk) aims to provide all the building blocks that are required to build large scale detection and ranking systems. Namely, the framework provides the following key components:

  • a distributed storage suited for very large datasets and BigData applications,
  • a web based visualization and management interface,
  • a distributed execution framework to reliably execute the detection algorithms and balance the compute load between multiple servers,
  • and an easy to configure triggering mechanism that allows to execute the detection algorithms when new data is available or when configured conditions are met.

All these components are implemented in a generic way. They are independent of the type of data that will be processed by the framework. This allows the data scientist to focus on his core business: developing effective detection algorithms.

Check GIT repository

MARk : Use built-in detectors

Now that you have a running MARk server, with data flowing in, you can use the provided algorithms to build your detection chain.

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Getting started with MARk : create a PHP data injector

The Multi-Agent Ranking framework (MARk) aims to provide all the building blocks that are required to build large scale detection and ranking systems. For this blog post we will use docker and docker-compose to run a MARk server, then we will use PHP and composer to inject data in the framework.

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Multi-Agent Ranking framework version 2 is out

This week we released a new major version of the Multi-Agent Ranking framework (MARk). This version brings two main changes:

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