The Dark Art: Is Music Recommendation Science a Science?

Moreover, by using the user feedback (selected songs from the recommendation list) to personalize the recommenda- tion model, increased the number of adequate songs for each activity

The prototype implements three algorithms to recommend concerts by taking advan- tage of what users have listened to before: a collaborative filtering algorithm (K-Nearest Neighbor),

Using this information, the personalized news recommendation works as follows: Given a target user who is reading a seed article, we recommend a set of news articles that (1)

In this instance, the purpose of user recommendation is to identify relevant people to follow among millions of users that interact in the social network.. Previous attempts in-

The evidence on demand response by level of care is mixed: in Ghana, hospital care is more price elastic than lower levels of care - the measure for inpatient care is in fact

When, the time-factor is disabled the user will retrieve news solely based on the other relevance factors (location and personal interests). Figure 2b shows an example of how

Since we are using an ex- tractive summary procedure, we make use of a classical loss used for summarization systems: we use a recall-oriented ROUGE-n metrics, by comparing

with a music retrieval system: (i) music search, when a user has an initial idea of what he/she wants, and operates with metadata to query for a specific artist, album, genre, etc.,