= Things to do =

 * '''Adaptation for music domain'''
   * finish skiptrax ontology (see [http://musicontology.com/ Music Ontology]) - 1-3 weeks
     * handle remixes/live/unplugged (song variants)
     * discern song and file - model file ownership
   * Proper GUI with the following functions:
     * metadata importers/exporters (ID3, LastFM, etc.) - 1-2 weeks
     * (adapter for own audio collection)
     * simplify entering song/band information - 1 week
     * (generate/play playlists, possibly with changing style over time (AutoDJ) - 2-6 weeks)
 * '''Metadata-based functionality'''
   * different sharing rights for contacts (e.g. A only ontologies, B also metadata, C everything) - <1 week
   * expert recommender (ask friends about people having knowledge about X/interests in Y) - 1-3 weeks
   * trust visualization
   * scalable algorithms - ''scalable'' = void algo(Graph oldFacts, Graph additionalFacts, Datastructure internalData, Notifications interestingThings)
     * computation of feature summaries - 1 week
     * feature/item similarity measure - 2 weeks
     * structured search (index)
     * implicit trust (= peer competence) metric - 2-5 weeks
     * explicit representation of trust (see Skippies ontology) - 2-5 weeks
       * user interface changes for that
       * trust metric changes for that
       * by combining computed and explicit trust ratings, identifying shared interests/fields of competence should be possible.



[RelatedWork]

= Ideas =

Skipforward is intended to provide content-bases recommendations, but there might be some cool variants of combining it with collaborative filtering/recommendation:


=== Collaborative filtering per feature ===

Instead of the boring "people who like this also like that" recommendations, this could be adapted in the following way:

People who like A also like B => People who think A has feature F also think that B has feature F[[BR]]
People who like the same items like you also like this => People who annotated items the same way as you annotated this that way

The last strategy could be used to rate items that haven't been reviewed by the user, but by his friends.