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TIIS-HDMRS 2012 : pecial Issue of the ACM Transactions on Interactive Intelligent Systems on HUMAN DECISION MAKING AND RECOMMENDER SYSTEMS


When N/A
Where N/A
Submission Deadline Feb 29, 2012
Notification Due May 29, 2023
Final Version Due Nov 26, 2012
Categories    information retrieval

Call For Papers

Call for Papers

Special Issue of the

ACM Transactions on Interactive Intelligent Systems on HUMAN DECISION MAKING AND RECOMMENDER SYSTEMS

Main submission deadline: February 29th, 2012


A primary function of recommender systems is to help people make good choices and decisions. But in research on recommender systems, surprisingly little attention has been devoted to the decision making processes of users. Instead, it has focused mainly on (a) ways of eliciting and modeling users' preferences and (b) algorithms for identifying items that a user is likely to evaluate positively. Even systems that do explicitly aim to support the decision making process could benefit from greater use of knowledge about human decision making. And the growing amount of research on users' interaction with recommender systems, which aims to enhance their usability and acceptance, can be expanded to consider support for specific aspects of decision making.

This special issue will highlight research that explicitly considers ways in which an understanding of human choice and decision making can benefit research and practice on recommender systems. The dimensions listed below indicate the range of work that is relevant to the special issue. In case of doubt about the relevance of your topic, please contact the special issue associate editors.


Types of Decision Made by Users of Recommender Systems

- Decisions about items in some domain (e.g., products,

documents, ...)

- Decisions about actions performed as part of the domain-level

decision making process (e.g., what information to divulge or

to acquire)

Aspects of the Recommendation Process

- Acquiring information about users' preferences

- Modeling users' preferences

- Provision of decision-relevant information

- Presentation and explanation of recommendations

- Adaptation to the interaction context

- Special characteristics of recommendation to groups

- ...

Aspects of Human Choice and Decision Making

- What people desire in a decision making process

- Roles of justification and argumentation in decision making

- Descriptive models of choice

- Heuristics and biases

- The nature of preferences

- Temporal aspects of decision making

- Forms of social influence

- Roles of emotion and mood

- Effects of learning from experience

- Negotiation in decision making

- Factors that influence decision making (e.g., culture, mood,

time pressure ...)

- ...

Evaluation Criteria for Recommender Systems

- Decision quality

- Minimization of effort and stress

- Trust and confidence

- ...

Nature of the Research Contribution

- Novel functionality inspired by an understanding of human

decision making

- Empirical results concerning decision making with recommender


- Innovation in research methodology (e.g., concerning ways of

evaluating recommender systems or observing users' decision

making processes)

- ...


- Alexander Felfernig, Graz University of Technology, Austria


- Francesco Ricci, Free University of Bozen-Bolzano, Italy


- Li Chen, Hong Kong Baptist University, China

- Giovanni Semeraro, Marco de Gemmis, and Pasquale Lops,

University of Bari Aldo Moro, Italy


- By February 29th, 2012: Submission of manuscripts

- By May 29th, 2012: Notification about decisions on initial


- By August 27th, 2012: Submission of revised manuscripts

- By October 26th, 2012: Notification about decisions on revised


- By November 26th, 2012: Submission of manuscripts with final

minor changes

- Starting December, 2012: Publication of the special issue on

the TiiS website, in the ACM Digital Library, and (shortly

afterward) as a printed issue


Please see the instructions for authors on the TiiS website (


TiiS (pronounced "T double-eye S") is a recently founded ACM journal for research about intelligent systems that people interact with. The journal's procedures and infrastructure have been designed to combine the traditional quality and depth of ACM journals with the efficiency and predictability of the best-run conferences.

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