ComplexRec 2017                                                                           Preface


Preface
This volume contains the papers presented at the RecSys 2017 workshop Recommendation in
Complex Scenarios (ComplexRec 2017) held on August 31, 2017 at the Villa Erba, in Como,
Italy.
    State-of-the-art recommenation algorithms are typically applied in relatively straightforward
and static scenarios: given information about a user’s past item preferences in isolation, can
we predict whether they will like a new item or rank all unseen items based on predicted
interest? In reality, recommendation is often a more complex problem: the evaluation of a
list of recommended items never takes place in a vacuum, and it is often a single step in the
user’s more complex background task or need. These background needs can often place a
variety of constraints on which recommendations are interesting to the user and when they are
appropriate. However, relatively little research has been done on how to elicit rich information
about these complex background needs or how to incorporate it into the recommendation
process. Furthermore, while state-of-the-art algorithms typically work with user preferences
aggregated at the item level, real users may prefer some of an item’s features more than others
or attach more weight in general to certain features. Finally, providing accurate and appropriate
recommendations in such complex scenarios comes with a whole new set of evaluation and
validation challenges.
    The current generation of recommender systems and algorithms are good at addressing
straightforward recommendation scenarios, but the more complex scenarios as described above
have been underserved. The ComplexRec 2017 workshop aims to address this by providing an
interactive venue for discussing approaches to recommendation in complex scenarios that have
no simple one-size-fits-all solution.
    The workshop program contains a set of position and research papers covering many complex
aspects of recommendation in various scenarios. There were 7 submissions. Each submission
was reviewed by at least 3 program committee members. The committee decided to accept 5
papers (acceptance rate 71%). The program also includes an invited keynote talk by Dietmar
Jannach (Technische Universität Dortmund).
    We thank the program committee members for their timely and constructive reviews. We
gratefully acknowledge the support of EasyChair for organizing paper submission and reviewing
and producing the proceedings.


August 11, 2017                                                                  Toine Bogers
Amsterdam                                                                       Marijn Koolen
                                                                            Bamshad Mobasher
                                                                                    Alan Said
                                                                            Alexander Tuzhilin




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