Sökning: "Music recommender"
Visar resultat 1 - 5 av 22 uppsatser innehållade orden Music recommender.
1. Framing theory on music streaming platforms : How vocabulary influences the user experience
Magister-uppsats, Jönköping University/JTH, Avdelningen för datateknik och informatikSammanfattning : Music streaming services aim to provide users with personalized content to avoid information overload and increase the user experience. Besides the recommender systems that are involved to ensure users are provided with their musical preferences, vocabulary can play a significant role in achieving personalization. LÄS MER
2. Assessing the Viability of Random Indexing in Song Recommender Systems
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis assesses how Random Indexing performs as a recommender system for music recommendations. Recommender systems have gotten more and more important as the amount of content provided gets larger and larger. They are usually focused on either product traits, and how they relate, or users and their past consumption. LÄS MER
3. What's in a name? How the vocabulary of personalised playlists affects user's expectation and satisfactions in music streaming services
Kandidat-uppsats, Jönköping University/JTH, Avdelningen för datateknik och informatikSammanfattning : Background: The following study focuses on the area of personalisation within streaming services and how vocabulary of playlist names and categories affect expectations and satisfactions. The wording of personalised items is important to convey that content is directly made for a user, yet there are limited studies that explore what users anticipate and if the message conveys correct information to then lead to satisfaction. LÄS MER
4. Algorithmic vs. Perceived Fairness in Music Recommender Systems : An Investigation of Popularity Bias from a User Perspective
Magister-uppsats,Sammanfattning : Recommender systems have the potential of helping users in finding relevant items in the online environment, and in many ways, they impact which content we consume. Thus, how fair these systems are affects us. A common fairness issue in recommender systems is popularity bias. LÄS MER
5. Finding time-based listening habits in users music listening history to lower entropy in data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : 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. LÄS MER
