For example, in a movie recommendation application, the story criteria rating
may have a very high “priority,” i.e., the movies with high story ratings are well
liked overall by some users, regardless of other criteria ratings. Therefore, if the
story rating of the movie is predicted high, the overall rating of the movie must also
be predicted high in order to be accurate.
The aggregation function approach consists of three steps, as summarized in
Fig. 24.1. First, this approach estimates k individual ratings using any recommendation technique. That is, the k-dimensional multi-criteria rating problem is