Changed tensor factorisation to als
Merge branch 'master' of github.com:ntnu-smartmedia/goldfish

# By Dag Einar Monsen
# Via Dag Einar Monsen
* 'master' of github.com:ntnu-smartmedia/goldfish:
  Add close method on KiwiRecommender.
  Add new datasets and discard unused MF code.
  Change recommendation weights to [1 2.5].
  Add movielens 1M synthesized dataset.
  Increase number of latent factors for tucker factorization.
  Disable debugging in matlab code. We don't want a random tensor.
  Enable evaluation of KiwiRecommender.
  Print RMSE in Result.java
  Rename Evaluation.getBuilder() to Evaluation.getRecommenderBuilder() and add Evaluation.getModelBuilder().
  Move Kiwi matlab constructor to ensure new objects are created when they are in Java.
  Update KiwiEvaluation. Implement DataModelBuilder() which is used by the IRevaluator.
  Update SMDataModel. Works out all earlier issues.
  Create interface SMPreferenceArray.
  Create SMDataSplitter to support SMDataModel and SMUserPreferenceArray.
  Create SMItemPreferenceArray and update SMUserPreferenceArray to reflect changes to SMDataModel.
  Covert SMPreference interface to abstract class and implement combineValues().
  Drop using delegate model in SMDataModel to give more control of processing.
  Change PreferenceView in SMUserPreferenceArray to support multiple values.
  Rename SMPreference class to GenericSMPreference and create interface SMPreference.

Conflicts:
	matlab/Kiwi.m