Mixing it up: recommending collections of items

ABSTRACT

Recommender systems traditionally recommend individual items. We introduce the idea of collection recommender systems and describe a design space for them including 3 main aspects that contribute to the overall value of a collection: the value of the individual items, co-occurrence interaction effects, and order effects including placement and arrangement of items. We then describe an empirical study examining how people create mix tapes. The study found qualitative and quantitative evidence for order effects (e.g., first songs are rated higher than later songs; some songs go poorly together sequentially). We propose several ideas for research in this space, hoping to start a much longer conversation on collection recommender systems.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.4 Systems and Software
          Subjects: Performance evaluation (efficiency and effectiveness)

General Terms:
Design

Keywords:
automatic playlist generation, collaborative filtering, collection recommender systems, collections, mix tape, music, playlist, recommender systems