FROM THE WEB: Could Machine Learning Be Used To Filter Online Content?

A recent TechCrunch article has revealed how researchers in Finland might have found a way to use machine learning to filter online content.

The article explains how researchers from the Helsinki Institute for Information Technology have been looking into how EEG (electroencephalogram) sensors and models designed to read them could be used to personalise content in the future.

The study asked participants to read Wikipedia articles while wearing an EEG cap, and this enabled the researchers to create a list of keywords that each person identified as informative.

The research therefore suggests that in the future, we might be able to use this kind of technology to suggest and filter content to individual users.

Researcher Tuukka Ruotsalo explains: “There’s a whole bunch of research about brain-computer interfacing but typically, the major area they work on is making explicit commands to computers.

“So that means that, for example, you want to control the lights of the room and you’re making an explicit pattern, you’re trying explicitly to do something and then the computer tries to read it from the brain.”

He added: “In our case, it evolved naturally – you’re just reading, we’re not telling you to think of pulling your left or right arm whenever you hit a word that interests you.

“You’re just reading – and because something in the text is relevant for you we can machine learn the brain signal that matches this event that the text evokes and use that.”

Reach TechCrunch’s full article here.