Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 75. Bestandsnummer des Verkäufers 26399637991
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. pp. 75. Bestandsnummer des Verkäufers 396771896
Anzahl: 4 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. pp. 75. Bestandsnummer des Verkäufers 18399637997
Anzahl: 4 verfügbar
Anbieter: Vedams eBooks (P) Ltd, New Delhi, Indien
Hardcover. Zustand: New. Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa. Bestandsnummer des Verkäufers 153610
Anzahl: 5 verfügbar
Anbieter: MK BOOK SERVICES, Huntingdon, Vereinigtes Königreich
Hardcover. Zustand: New. Bestandsnummer des Verkäufers ABE-1735039317089
Anzahl: 1 verfügbar