Simplified Evaluation of Recommendation

Separated components to simplify setting up evaluation of recommenders.
Added skeleton for RESTful endpoints to access movie data

Added post, put, and delete for a movie resource.
Added non personalized top-n recommender with id rescorer

Calculates top-n movie recommendations but takes into consideration
number of ratings a movie has received.
Added new time based evaluation

Stopped using ReloadFromJDBCDataModel since it does not keep timestamp
of a preference. Added first version of a time based evaluation that
evaluates recommendations at the time of a user u’s rating at time t
Renamed MovieApi to MovieDAO

Use MovieDAO to respond to HTTP requests from resources and return
responses to client
Custom item average recommenders

Experimented with implementing non personalized recommenders with built
in id rescorers. Also created a multiple id rescorer class.
Created new packages

Organized the project with new packages and moved appropriate classes.
Time based evaluation

Experimenting with introducing user preferences at different timestamps
to data models and evaluating different recommender systems with these
data models.