============
Call for papers
============
Journal: International Journal of Multimedia Information Retrieval
Special Issue: Multimedia Recommendation Systems
Special Issue Editors: Dr. Yashar Deldjoo and Dr. Markus Schedl
Deadline: October 1, 2019

http://www.cp.jku.at/journals/ijmir_2019_cfp.html

==================
Special issue summary
==================.

Recommendation systems have become a crucial means to manage the ever 
increasing amount of multimedia content available today, and to help users 
discover interesting new items. While the recommender systems and the 
multimedia communities have researched great tools to address problems in their 
areas, the innovative combination of state-of-the-art recommender systems 
technology and multimedia content analysis to build content-based and hybrid 
recommendation systems for media or other items has not been subject of a wider 
discussion yet. With this Special Issue we aim to bridge this gap between 
communities and provide a venue for exciting new research on recommender 
systems that leverage multimedia content.

We solicit original research that either use multimedia content (e.g., audio, 
visual, textual content) to recommend media items (e.g., movies, music, images) 
or non-media items (e.g., fashion products or e-commerce products). Also hybrid 
and context-aware recommendation approaches are welcome, as long they leverage 
at least one content modality, irrespective of its representation, e.g., 
including raw signal data as well as semantic descriptors extracted from 
knowledge bases or graphs. Purely CF-based methods are out-of-scope.

Topics of interest include the following:

  *   Hybrid recommendation systems for multimedia content
  *   Deep learning from multimedia signals for recommendation systems
  *   Improving session-based recommendation systems by content models
  *   Combating cold-start by leveraging multimedia content
  *   User modeling and profiling for multimedia recommendation (including use 
of knowledge bases or graphs)
  *   Improving beyond-accuracy performance of recommender systems through 
multimedia (e.g., diversity, coverage, serendipity)
  *   Studies on the human understanding and perception of multimedia content 
with direct implications on recommender systems
  *   Predicting and integrating user intent into multimedia recommendation
  *   Using multimedia content for transparent and/or fair recommendations
  *   Privacy-aware recommendation (complying to the general data protection 
regulation)
  *   New evaluation metrics for content-based multimedia recommender systems
  *   New datasets accompanied by solid case studies of their application
  *   Novel (or under-researched) applications areas of content-based 
recommender systems (e.g., podcast, speech, health, art, or fashion 
recommendation)


=================
Manuscript submission
=================

We encourage original submissions of excellent quality that are not submitted 
to or accepted by any other journal or conference. Substantially extended 
versions of conference or workshop papers (at least 30% novel content) are 
welcome as well. Papers should not exceed 14 pages in the Springer 
double-column format.

All submissions to this Special Issue will be peer-reviewed by at least three 
members of the Guest Advisory Board. The review process will be single-blind. 
After a first review cycle, we will select according to the reviewing results a 
small number of submissions which might be considered for acceptance. In a 
second review cycle the authors of the selected submissions will have the 
chance to modify their submissions according to the reviewers suggestions, 
before a final decision for acceptance or rejection will be made.

Submissions will be managed by Springer Editorial Manager. Please create a user 
account if you have not already done so, login and follow the instructions to 
submit a new contribution.


--
Yashar Deldjoo, PostDoctoral Researcher
Polytechnic University of Bari (Politecnico di Bari), Italy
Department of Electrical Engineering and Information Technology
Information Systems Laboratory Laboratory (SisInf Lab)
Email: deldj...@acm.org
http://www.ydeldjoo.me
--

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