In our highly data-driven environment, businesses are essentially becoming semi-autonomous agents, constantly competing for resources, customers and talent.
How can they adapt and remain competitive in an ever-changing market?
What techniques could leverage real-time data to boost their customer acquisition process?
How can they learn about their competition, when the competition is learning them?
Can the effects of business decisions on the eco-system be anticipated?
To answer those questions, I will present machine learning and text mining techniques, that mine data from heterogeneous sources,
to predict in such multi-agent temporal environments.
Dr. Radinsky is the CTO and cofounder of SalesPredict, a sales technology company, where she is pioneering artificial intelligence based, predictive analytics solutions that transform the way companies do business.
Dr. Kira Radinsky is one of the up and coming voices in the data science community, pioneering the field of Web Dynamics and Temporal Information Retrieval. Her work focuses on the intersection of predictive data mining and the construction of algorithms that leverage web-found information and external dynamics to predict future events. A graduate of the Technion-Israel Institute of Technology, Dr. Radinsky gained international recognition for her work there and at Microsoft Research where she developed predictive algorithms that recognized the early warning of globally impactful events, (e.g. riots or diseases.)
In 2013, Kira Radinsky was named to the prestigious “35 Young Innovators Under 35”, as chosen by the MIT Technology Review.
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