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Showing result 1 - 5 of 13 essays matching the above criteria.
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1. Unboxing The Algorithm : Understandability And Algorithmic Experience In Intelligent Music Recommendation Systems
University essay from Malmö universitet/Institutionen för konst, kultur och kommunikation (K3)Abstract : After decades of black-boxing the existence of algorithms in technologies of daily need, users lack confidence in handling them. This thesis study investigates the use situation of intelligent music recommendation systems and explores how understandability as a principle drawn from sociology, design, and computing can enhance the algorithmic experience. READ MORE
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2. Finding time-based listening habits in users music listening history to lower entropy in data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In a world where information, entertainment and e-commerce are growing rapidly in terms of volume and options, it can be challenging for individuals to find what they want. Search engines and recommendation systems have emerged as solutions, guiding the users. READ MORE
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3. Automatic Music Recommendation for Businesses : Using a two-stage Membership model for track recommendation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis proposes a two-stage recommendation system for providing music recommendations based on seed playlists as inputs. The goal is to help businesses find relevant and brand-fit music to play in their venues. READ MORE
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4. Content-based music recommendation system : A comparison of supervised Machine Learning models and music features
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : As streaming platforms have become more and more popular in recent years and music consumption has increased, music recommendation has become an increasingly relevant issue. Music applications are attempting to improve their recommendation systems in order to offer their users the best possible listening experience and keep them on their platform. READ MORE
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5. Music Recommendations; Approximating user distributions to address the cold start problem
University essay from Lunds universitet/Statistiska institutionenAbstract : In today's data driven society the world is at a point of information overload. As people rely on Google for information and other platforms such as Netflix and Spotify for entertainment, the need for relevant filtering of content has never been higher. As a result, recommendation systems have seen a great surge in demand. READ MORE