New Algorithms Could Reduce Polarization Driven By Information Overload | News & Events

As the volume of available information expands, the fraction a person is able to absorb shrinks. To break this cycle, computer scientists say we need new algorithms that prioritize a broader view over fulfilling consumer biases.

Source: New Algorithms Could Reduce Polarization Driven By Information Overload | News & Events

What’s your brand? | The University of Tokyo

Researchers created an algorithm that successfully predicted consumer purchases. The algorithm made use of data from the consumers’ daily activity on social media. Brands could use this to analyze potential customers. The researchers’ method combines powerful statistical modeling techniques with machine learning-based image recognition.

Source: What’s your brand? | The University of Tokyo

UNIVERSIS: Ένα ανοιχτό λογισμικό για την διαχείριση Ηλεκτρονικής Γραμματείας Ακαδημαϊκών Ιδρυμάτων – Ανοιχτές Τεχνολογίες στην Εκπαίδευση

Source: UNIVERSIS: Ένα ανοιχτό λογισμικό για την διαχείριση Ηλεκτρονικής Γραμματείας Ακαδημαϊκών Ιδρυμάτων – Ανοιχτές Τεχνολογίες στην Εκπαίδευση