Describes how broad recommendations produced by a recommender system For example, a recommender that suggests only next book in series is less diverse than a recommender that can recommend books from other series To calculate diversity:
- Calculate similarity between items
- Calculate average similarity between recommendations in top-n list ()
- Diversity is opposite of similarity, so to get it subtract from ()
Unusually high diversity could mean bad recommendations