In conjunction with AAAI 2014
July 27/28, 2014 - Quebec, Canada

http://ls13-www.cs.uni-dortmund.de/homepage/itwp2014/

Submission Deadline: April 10, 2014
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Web Personalization and recommendation systems have been steadily gaining
ground as essential components of today's Web based applications, including
in e-commerce and customer relationship management, in the delivery of
business services, in providing support for Web search and navigation, and
in reducing cognitive overload in information rich interactive social Web
applications. The proliferation of Web 2.0 applications has allowed users to
go beyond simple consumers of information and instead actively participate
in shaping collaborative environments in which users, resources, and
user-provided content are all networked together. This, in turn has
increased the need for more intelligent and personalized services that help
users interact with and navigate these complex information spaces. These
include a new generation of recommender systems that integrate multiple
online channels, are more scalable, are more adaptive, can better handle
user interactivity, and are more adept at user preference elicitation. To
achieve this, such applications must rely on intelligent techniques from AI,
machine learning, Web mining, statistics, and user modelling in order to
leverage all available data, including the usage and click-stream data
(reflecting user behaviour), the content and meta-data associated with
resources, semantic domain knowledge, user profile information, and
underlying network structures. Efficient and intelligent techniques are
needed to mine this data for actionable knowledge, and to effectively use
the discovered knowledge to enhance the users' experience.

The aim of this workshop is to bring together researchers and practitioners
from Web Mining, Web Personalization, Recommender Systems, and User Modeling
communities in order to foster an exchange of information and ideas and to
facilitate a discussion of current and emerging topics related to the
development of intelligent Web personalization and Recommender Systems.

TOPICS OF INTEREST

We invite original contributions in a variety of areas related to Web
personalization and Recommender Systems:

* User model representation and preference elicitation: Knowledge
acquisition strategies, user context modeling, cross-domain models, privacy,
cognitive models for Web navigation, self-adaptation, utility function
elicitation from user interaction, user modeling on the Social Web;

* Architectures, systems and enabling technologies: personalized search,
scalability of personalization and recommendation techniques for "Big Data",
intelligent browsing and navigation, adaptive hypertext systems, hybrid and
conversational recommendation systems, context-awareness, Data/web mining
for personalization, Link Analysis and Graph Mining, automated techniques
for ontology generation, learning, and acquisition; machine leaning
techniques for information extraction, Social Web, and the Semantic Web;

* User and algorithm centric evaluation methodologies, metrics, and case
studies

PAPER SUBMISSION AND PARTICIPATION

Papers must be formatted according to the AAAI 2014 style guide
(http://www.aaai.org/Publications/Author/author.php) and submitted
electronically as PDF to itwp2014@ls13.cs.uni-dortmund.de. We solicit long
and short papers as well as research demos. Long papers (7 pages) present
original research work; short papers (4 pages) report on work in progress or
describe demo systems.

The workshop proceedings will be published as citable AAAI technical report
in the AAAI digital library.

IMPORTANT DATES

* 10 April: Paper submission deadline
* 1 May: Author notification
* 15 May: Camera-ready versions due
* 27/28 July: Workshop held

WORKSHOP ORGANIZERS

Dietmar Jannach, Department of Computer Science, Technische Universität
Dortmund, Germany
E-mail: dietmar.jannach@tu-dortmund.de

Bamshad Mobasher, School of Computer Science, DePaul University, Chicago,
USA
E-mail: mobasher@cs.depaul.edu