[Asis-l] Deadline extension - Special issue on Advances in Computer-Human Interaction for Recommender Systems

[Ludovico Boratto]

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Submission deadline has been extended to May 15, 2017
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*Special Issue on "Advances in Computer-Human Interaction for Recommender
Systems"*
*International Journal of Human-Computer Studies (Elsevier)*

*CALL FOR PAPERS*
Recommender Systems produce suggestions to users for items or contents
based on user profiles, users’ explicit or implicit feedback, which the
users might have not originally considered but might be of interest to
them. Such recommendations are produced by analyzing what they previously
consumed (bought, watched, or listened) or by the identification of
similarities with other users. Such an explicit feedback is usually an
expression of extreme ratings, either positive or negative. In the middle
of the range stays a set of different actions in the interface that might
be interpreted as feedback, but that needs to be collected *implicitly*.
Even if the literature provides different techniques for collecting
implicit feedbacks, they are usually tailored to specific types of
applications.
>From the user's point of view Recommender Systems remain a black box that
suggests objects or contents, but the users hardly understand *why* some
items are included in the suggestion list. Providing the users with an
understandable representation of how the system represents them and
allowing them to control the recommendation process would lead to benefits
in how the recommendations are perceived and in the capability of the
system to be persuasive. Such transparency is one of the multiple (and
usually conflicting) requirements of Recommender Systems.
Beyond the classical engineering of Recommender Systems focusing on data
processing, filtering and sorting, the engineering aspects should also
cover aspects related to how users interact with it, including how to input
data, how to define and evolve the user model, how to present the
information to the users and how the users can manipulate that
information.  Such engineering processes might benefit from practice in
specific areas, such as web configurators (which guide the users in the
inspection of possible product variants) and safety critical interactive
systems (where predictability and consistency over executions are
prerequisite to certification). In order to deploy Recommender Systems in
broader contexts, there is a need for structured and systematic approaches
to engineer such complex computing systems.
This special issue solicits novel papers on a broad range of topics,
including, but not limited to:

   - *NOVEL APPLICATION DOMAINS*
      - Critical systems;
      - 3D, Augmented and Virtual Reality;
      - End User Development;
      - Other novel applications.
   - *USER INTERFACES FOR RECOMMENDER SYSTEMS*
      - Differences and analogies between UIs for recommender systems,
      expert systems,  and configuration systems;
      - Identifying and managing conflicts between the properties of the UI
      and properties of the Recommender Systems;
      - Transparency of the recommendation process and creation of
      interactive handles for supporting user’s control;
      - New interactions for consuming and guiding recommendation
      (gestures, tangible interaction etc.);
      - Analysis of feedback based on small exposures on the item itself:
      photos, trailers etc.
   - *RECOMMENDER SYSTEMS CORE*
      - Exploit the user interaction to enrich recommendation models based
      on latent factors;
      - Real  time aspects of recommendations: view updates, user’s
      awareness, balance between recommendation, and task focus/goal,
worst case
      execution time analysis;
      - Recommendation effectiveness beyond business focused metrics: how
      to evaluate them, suitable classifiers;
      - Creating forms of elicitation and enabling user control to improve
      the perception of the recommendations.
   - *EXPECTED PROPERTIES OF A RECOMMENDER SYSTEM*
      - Software architectures for usable recommender systems;
      - Guidelines for building trust in recommendations;
      - Solutions for enabling users and systems to work with large data;
      - Representation of performance issues.

*IMPORTANT DATES*
•    Manuscript submission due: *May 15, 2017*
•    First round decision made: *July 31, 2017*
•    Revised manuscript due: *September 30, 2017*
•    Final decision made: *November 15, 2017*
•    Final paper due: *December 15, 2017*

*SUBMISSION GUIDELINES*
Paper submissions must conform to the International Journal of
Human-Computer Studies format guidelines
<https://www.elsevier.com/journals/international-journal-of-human-computer-studies/1071-5819/guide-for-authors>
.
Manuscripts must be submitted to the online submission system
<http://ees.elsevier.com/ijhcs/> (select option SI:AdCHIReS in the article
type section).
Submissions to this Special Issue must represent original material that has
been neither submitted to, nor published in, any other journal. A
submission based on one or more papers that appeared elsewhere should have
at least 50% of novel valuable content that extends the original work (the
original papers should be referenced and the novel contributions should be
clearly stated in the submitted paper).

*CONTACTS*
For enquires regarding the special issue, please send an email to both the
guest editors at davide.spano at unica.it and ludovico.boratto at acm.org.

*GUEST EDITORS*
Lucio Davide Spano (University of Cagliari, Italy)
Ludovico Boratto (Eurecat, Spain)