Finding the needle in a haystack: extracting information from Big Data

Generating novel methods to deal with the complexity of pattern recognition tasks

Big Data is emerging as one of the major technical and business challenges across many sectors including industrial, commercial and health care. More and more data is being gathered, from increasingly diverse systems. How can we analyse all this data?

Research undertaken by the Advanced Computer Architectures research group at the University of York has generated novel methods to deal with the complexity of pattern recognition tasks. These methods are now allowing businesses to generate intelligence from their raw data. Building on binary neural techniques – called associative memories – these tools provide the capability to drill down into data and to look for pattern based events on data collected from sensors on monitored systems.

https://www.youtube.com/watch?v=4Y43qrC_P6k

  • Developed by the Advanced Computer Architectures research group
  • Researchers included Professor Jim Austin and Dr Tom Jackson
  • Technology: Data mining and pattern recognition software
  • The technology has been developed and used by a spin-out company, Cybula. Cybula are still based within the Department of Computer Science.
  • Impact: The software and methods developed have now been used in many industries, including power generation; oil and gas; water; transport; healthcare and image analysis and 3D facial recognition.

 

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