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Online Machine Learning Methods - Streams of Financially Important News.

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If you have a question about this talk, please contact Jan Samols .

Twitter nowadays is more than just stories about cats in trees and what I had for dinner. It is now a serious source of market moving news – stories on Twitter that can cause real changes in stock markets.

But with hundreds of millions of posts per day, how can we quickly identify stories that matter to our clients?

I will sketch how we used online machine learning methods to find and organise incoming stories into real time streams of related content, processing more than 8k tweets per second on a single core. Along the way I will talk about open problems such as trust, multilinguality and market manipulation.

This talk is part of the Technical Talks - Department of Computer Science and Technology series.

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Goldsmiths 1, Lecture Theatre, Department of Materials Science & Metallurgy Engineering Department - James Dyson Building Seminar Room MR11 (Malcolm Room), Pavilion B, DAMTP, CMS

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