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*Special Sesssion on Human Factors in Information Retrieval and 
Recommender Systems*

As part of The International Symposium on Methodologies for Intelligent 
Systems (ISMIS 2012)
Macau, China, 4-7 December 2012

*[Scope and Objectives] *

Through numerous research programs, competitions, and economic surveys, 
automated information retrieval systems and recommender systems have 
been proven to be ef´Čücient and useful by reducing the cognitive load and 
time required during the search and access to data. Over the past two 
decades of research within this field, this improvement of 
human-computer interactions is mainly relying on increasing systems' 
accuracy at different levels. Usage mining techniques aim at inferring 
accurate preferences, habits, and interests and building profiles from 
users' actions. Collaborative and content-based filtering make use of 
these profiles to provide users with relevant recommendations. 
Ontology-based systems formally define concepts within a domain, thus 
reducing ambiguity. All these machine learning models and algorithms are 
evaluated relatively to true risk and empirical risk, leading to very 
accurate contents. Yet, a crucial aspect is missing within these 
evaluation metrics. It does not take into account human factors playing 
a role within the decision process. Even the most relevant information 
is not sufficient to maximize users' acceptance/adoption rate, and 
satisfaction. The time has come to design holistic intelligent systems 
that provide the right information at the right time, in the correct 
manner, in agreement with users' policy and with valuable arguments. New 
challenges consist in: (1) identifying human factors that play a role 
within decision making an/or maximize users' acceptance, adoption and 
satisfaction, (2) integrating these factors in machine learning 
algorithms, (3) designing interfaces to improve human-computer 

*[Topics of interest]*
Topics of interest include (but are not limited to) the following:
- Human factors and decision making (diversity, personality, emotions, 
mood, culture, ...)
- Preserving privacy while modeling users and recommending items
- Trust and reputation
- Context and information retrieval
- Impact of recommenders on decision process
- Multi-criteria optimization (privacy vs. accuracy, diversity vs. 
similarity, scalability vs. time constraints, ...)
- User studies (identifying human factors, evaluation of recommender 
- Social influence (leaders, explicit and implicit social networks, 
maximizing acceptance, manipulation...)
- User-centered design and adaptation of interfaces
- Presentation and explanations in recommender systems
- Visual representation of data

*[Paper Submissions]*
Authors are invited to submit original unpublished manuscripts that 
demonstrate current research on one or several of the special session 
topics of interest. Papers should be prepared using the Springer 
LNCS/LNAI style with a maximum of 10 pages. All submitted papers will be 
reviewed by the following program committee of this session.

Paper should be submitted in PDF form via ISMIS 2012 Online Submission 

While submitting the paper, please remember to mark as part of the 
"Special Session on Human Factors in Information Retrieval and 
Recommender Systems".

*[Important Dates] *
Electronic submission of full papers : June 1, 2012
Notification of paper acceptance : August 1, 2012
Camera-ready of accepted papers : August 31, 2012
Conference : December 5-7, 2012

*[Special Session Organizers] *
Anne Boyer, LORIA, Lorraine University, France
Sylvain Castagnos, LORIA, Lorraine University, France

*[Program Committee]*

  * Anne Boyer (LORIA, Lorraine University, Nancy - France)
  * Shlomo Berkovsky (CSIRO, TasICT Centre, Hobart - Australia)
  * Robin Burke (DePaul University, Chicago - USA)
  * Sylvain Castagnos (LORIA, Lorraine University, Nancy - France)
  * Li Chen (Hong Kong Baptist University, China)
  * Nathalie Denos (LIG, Grenoble - France)
  * Patrick Gallinari (LIP6, Paris - France)
  * Dietmar Jannach (University of Dortmund, Germany)
  * Alfred Kobsa (University of California, Irvine - USA)
  * Judith Masthoff (University of Aberdeen, Scotland - UK)
  * Cecile Paris (CSIRO ICT Centre, Australia)
  * Liana Razmerita (CBS, Copenhagen - Denmark)
  * Francesco Ricci (University of Bozen-Bolzano, Italy)
  * Michael Thelwall (University of Wolverhampton, UK)

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