Constructing a genre-based recommendation system: enhancing music discovery through feature similarity
Nayebkhil, Iraj (A.A. 2023/2024) Constructing a genre-based recommendation system: enhancing music discovery through feature similarity. Tesi di Laurea in Introduction to computer programming, Luiss Guido Carli, relatore Alessio Martino, pp. 24. [Bachelor's Degree Thesis]
![[img]](http://tesi.luiss.it/style/images/fileicons/application_pdf.png) |
PDF (Full text)
Restricted to Registered users only Download (3MB) | Request a copy |
Abstract/Index
Literature review. Methodology and development. Discussion. Evaluating the recommendation system. Limitations. Area of further research.
References
Bibliografia: pp. 20-21.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Introduction to computer programming |
| Thesis Supervisor: | Martino, Alessio |
| Academic Year: | 2023/2024 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 26 Nov 2024 10:28 |
| Last Modified: | 26 Nov 2024 10:28 |
| URI: | https://tesi.luiss.it/id/eprint/40417 |
Downloads
Downloads per month over past year
Repository Staff Only
 |
View Item |
