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Subject:

Deadline Extention: Workshop on Trust, Reputation and User Modeling (TRUM)

From:

Jie Zhang <[log in to unmask]>

Reply-To:

Jie Zhang <[log in to unmask]>

Date:

Sun, 17 Apr 2011 21:31:39 -0400

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (121 lines)

Deadline of the Workshop on Trust, Reputation and User Modeling (TRUM)  
has been extended till April 25, 2011.

------------------------------------
Workshop on Trust, Reputation and User Modeling (TRUM)
With UMAP'2011, Girona, Spain, July 11, 2011

http://madmuc.usask.ca/WS-TRUM/

----------------------------------------------------------
Important Dates:
April, 15 2011: Deadline for workshop paper submissions.
May, 13 2011: Notification to Authors of accepted papers.
May, 31 2011: Camera ready.

----------------------------------------------------------
Objectives and Topics:

The first Trust, Reputation and User Modeling (TRUM) workshop pursues
the following specific objectives:
o To bring researchers together from the communities of trust and
reputation modeling and user modeling;
o To initiate and facilitate discussions on the new trends in trust,
reputation and user modeling, and to move the trends forward.
o To provide a forum for cutting-age research

There are three ways in which the area of user modeling and the area
of trust and reputation modeling overlap.

First, decentralized and ubiquitous user modeling has sought inspiration
from research in multi-agent systems over the last 6 years, resulting
in a series of workshops at the UM conference in 2005, 2007 and UMAP 2009.
The current trend towards software apps using the cloud to store and
process information that can be downloaded on social networks and mobile
devices platforms brings new importance to the area of decentralized user
modeling. Frameworks for dynamic and purpose based sharing of user model
fragments among apps needs to take into account the trust among these
apps. The trust of one agent in another can be viewed as a simple user/agent
model. Researchers in the area of trust and reputation mechanisms have
studied for many years techniques allowing autonomous agents and peers
to share, aggregate and make decisions based on these simple user models.
User modeling researchers can gain useful insights from this area.

Second, the area of trust and reputation modeling has experienced rapid
growth in the past 7 years. Recently, two important trends have been
emerging in this area. One is the computational modeling of agents' cognition,
such as subjectivity and disposition, to achieve more accurate trust and
reputation modeling. Another trend is modeling of agents' trust using a
stereotype approach to deal with the problem of lack of experience. Both of
these trends are closely related to studies in user modeling. The evidential
success of these new trends inspires and encourages researchers in the
trust community to make use of the rich literature in user modeling to
develop more comprehensive trust and reputation modeling approaches.

Finally, a third important way in which research in user modeling overlaps
with trust is the user?s trust in the adaptive / personalized application.
In effect it is a symmetrical area to that of user modeling: while user
modeling suggests that the system models the user, here the user models the
system. It relates to issues of user?s understanding of the application,
and of the privacy and integrity of the user model data, both of which are
actively studied in the user modeling community. Facilitating the user?s
understanding and trust in the system?s functioning and the way it manages
the user?s data is very important, since it determines the user?s acceptance
of the application?s recommendations or persuasion, the user?s satisfaction
with the application?s functionality, and ultimately, its success.

Topics to be covered in this Workshop include but are not limited to:

Trust and Reputation Modeling
- Subjectivity and Disposition in Trust and Reputation Modeling
- Cognitive and Computational Trust
- Stereotype-based Trust Modeling
- Trust in Social Networks
- Trust-based Recommender Systems
- Trust and Reputation Modeling in Mobile Networks
- Trust in Organizations, Institutions and Systems
- Models and mechanisms for privacy

User Modeling
- Decentralized User Modeling approaches
- Purpose-based user modeling
- Sharing of User model fragments
- User modeling in mobile computing, e.g. smart phone apps, vehicles, cameras
- User Modeling in ambient and ubiquitous computing
- User modeling in Social Networks
- Modeling evolving trust relationships among users in social networks
- Modeling evolving trust or distrust of users in applications
(privacy, integrity of user data)
- Modeling trust of users in recommenders and persuasive applications.

----------------------------------------------------------
Tentative Committee:

Julita Vassileva, University of Saskatchewan, Canada
Jie Zhang, Nanyang Technological University, Singapore

Lora Aroyo, Free University of Amsterdam, The Netherlands
Susan Bull, University of Birmingham, UK,
Robin Cohen, University of Waterloo, Canada,
Anwitaman Datta, Nanyang Technological University, Singapore,
Ralph Deters, University of Saskatchewan, Canada,
Ali Ghorbani, University of New Brunswick, Canada,
Steve Marsh, Communications Research Centre, Canada,
Judith Mashoff, University of Aberdeen, UK,
Murat Sensoy, University of Aberdeen, UK,
Aaditeshwar Seth, Indian Institute of Technology Delhi, India,
Thomas Tran, University of Ottawa, Canada,
Yang Wang, Carnegie Mellon University, USA

----------------------------------------------------------
Submission Guidelines:

All submissions should be no longer than 12 pages in LNCS format. Please
submit your paper on the TRUM Workshop Easychair site. All papers must be
submitted in either Adobe Portable Document Format (PDF), or Microsoft Word
Format (doc). All papers must be original and must not have been published
or under review elsewhere. Submissions will be reviewed for relevance,
originality, significance, validity and clarity. All articles selected for
publication will be reviewed by at least two reviewers with
expertise in the area.

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