1. A recommendation apparatus, comprising: adjustment information storage means for generating and storing adjustment information, the adjustment information mapping a value, resulting from multiplying a component similarity between a component in user preference information and a component in item preference information by a weight coefficient, to a target of an evaluation value determined in response to a type of an operation performed by a user on an item, the user preference information representing a preference of the user and constructed as a vector containing a plurality of components and the item preference information generated based on metainformation of each item serving as a target for recommendation and containing components of the same number as the number of components of the user preference information; multiple regression analysis means for calculating each weight coefficient on a per user basis through a multiple regression analysis based on a plurality of pieces of adjustment information, each component of the user preference information being multiplied by the respective weight coefficient; weight coefficient storage means for storing the calculated weight coefficient on a per user basis, each component of the user preference information being multiplied by the respective calculated weight coefficient in the calculation of the evaluation value; and recommendation item identifying means for identifying the item to be recommended to the user based on each component of the user preference information and the item preference information and the evaluation value calculated based on the weight coefficient responsive to the component.