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RIAO 2010 : 9th RIAO Conference Adaptivity, Personalization and Fusion of Heterogeneous Information


When Apr 28, 2010 - Apr 30, 2010
Where Paris, France
Submission Deadline Dec 18, 2009
Notification Due Feb 5, 2010
Final Version Due Mar 1, 2010
Categories    NLP   information retrieval

Call For Papers

First Call for Papers RIAO 2010 - 9th RIAO Conference Adaptivity,
Personalization and Fusion of Heterogeneous Information 28-30 April, 2010
Paris, France (Bibliotheque Nationale de France)

Important dates:

* Paper submission deadline December 18th 2009, midnight UTC + 1
* Notification to authors February 5, 2010
* Camera-Ready copies due March 1, 2010
* Conference dates April 28-30, 2010


The RIAO conference is a triennial conference, which addresses research
topics related to the design of robust and large-scale scientific and
industrial solutions to information processing.
Previous RIAO editions were held at Grenoble (1985), MIT (1988), Barcelona
(1991), Rockefeller University (1994), Montreal (1997), Paris (2000), and
Avignon (2004), and Carnegie Mellon University (2007).
Past RIAO conferences were constituted by both peer-reviewed scientific
sessions and demonstrations of innovative industrial applications and
advanced research prototypes.

Scope of RIAO 2010
Submissions are invited which present recent, original and unpublished
research on the theme of RIAO 2010: adapting, personalizing and merging
heterogeneous information.

Submissions may address one or more of the following subjects:

Information filtering
* Content based filtering
* Collaborative filtering
* Recommender systems
* Spam, protection of minors
Social networks
* Folksonomies, tagging
* Blogs
* Social search
* Communities
* Opinion and sentiment
Personalized IR and User modelling
* Adaptive IR
* Collaborative IR
* Interfaces
Information fusion
* Mash Ups
* Aggregated search
* Systems for watch, business decision
Formal models, theory
Information extraction and natural language processing, multilinguality
* Summarization
* Question answering
* Entity/relation extraction
* Cross-Language IR, Machine translation for IR Multimedia Information
* Image IR
* Video IR
* Speech/audio IR
* Music IR, analysis of multimedia content Web Search and Advertising
* Adversial IR
* Advertising
* Link analysis
* Cultural heritage
* Trademark search
* Scientific media
* Bio-computing and medical
* Database offloading

Evaluation, benchmarking

Machine Learning for IR
* Learning to rank
* Probabilistic topic models
* All kinds of learning techniques applied to IR

Program Chairs
Gabriella Pasi (Europe)
Tie-Yan Liu (Asia)
Prabhakar Raghavan (Americas)

Paper Submission

We welcome submissions from both research and industrial communities
addressing the main conference theme.
Submitted papers must describe an unpublished original work, emphasizing
completed or advanced research, possibly with releted experiments.
A parallel submission to other venues should be clearly indicated to the
program committee.
The submissions (which have to be blind) will be reviewed by at least three
program committee members. The submissions will be evaluated on the basis of
originality, relevance, technical quality, and presentation.
Papers can be submitted in two categories: full papers and short papers,
where full papers are appropriate for describing substantial research with
related evaluations and short papers will typically describe ongoing
research and preliminary results. All accepted papers in both categories
will be published in the conference proceedings. At the conference, full
papers will be presented as a talk and short papers will be presented as a
Long papers must not exceed 12 pages (5000 words), in one column format,
starting with an abstract.
Short papers must not exceed 6 pages (2500 words), in one column, starting
with an abstract.
Submissions should be in Microsoft Word format or in PDF.

The conference proceedings will be available to conference attendees, and
through the CID after the conference.

RIAO'2010 : Recherche d'Information Assistée par Ordinateur / Adaptativity,
Personalization and Fusion of Heterogeneous Information

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