Business Hypothesis: A ‘skill map’ of employees built on a machine-learning powered platform that analyses employee’s skills and makes them easily locatable will make knowledge sharing and management in companies substantially more effective. An internal system that allows employees to find the right internal skill and knowledge when they need it whilst providing data on skill gaps, needs and distribution across the organisation to management will fill this gap in the market.
The central value proposition of OwlMaps is our proprietary skill ranking process. This process builds upon existing machine learning and data analysis algorithms and combines them in a new way in order to build software that understands not just the fact that certain words are skills, but also how certain skills correlate with each other.
This process can serve as an engine to analyze, extract and search skills from any form of text generated by people, including but not limited to chat conversations, emails and CVs. Since the process is based on an unsupervised learning algorithm it can adjust itself to the needs of the target customer, thus enabling it to learn a client specific jargon.
Initial tests on a primitive version have found connections like:
● Quantum Mechanics, General Relativity, Physics
● ReactJS, EmberJS, RiotJS
● Keras, deeplearning4j, Torch Demo: https://www.youtube.com/watch?v=-61pB-hNDgc&feature=youtu.be
In case of serious interest, we can also run a live test.