[Asis-l] UM'03 Workshop on ML,IR and UM (merged with ML4UM workshop
Elaine Toms
Toms at fis.utoronto.ca
Wed Jan 22 18:02:17 EST 2003
MLIRUM'03: The Second Workshop on Machine Learning,
Information Retrieval and User Modeling
http://www.cs.rutgers.edu/mlirum/mlirum-2003
at the Ninth International Conference on User Modeling
http://www2.sis.pitt.edu/~um2003/index.html
June 22-26, Pittsburh, PA, USA
CALL FOR PAPERS
------------------------------------------------------------------------
HISTORY
At UM97, a first workshop on "Machine Learning for User Modeling"
(ML4UM) took place, and a special interest group was initiated. The
second ML4UM workshop was held at the UM99 and the Third at the
UM2001. The ML4UM SIG now has both a web site and a mailing list. At
UM2001, the first workshop on "Machine Learning, Information Retrieval
and User Modeling" (ML,IR, and UM) took place. We have merged these
two workshops and SIGs, as they have such related topics.
------------------------------------------------------------------------
BACKGROUND AND MOTIVATION
User model acquisition is a difficult problem. In Machine Learning,
the information available to a user modeling system is usually
limited, and it is hard to infer assumptions about the user that are
strong enough to justify non-trivial conclusions. Classical
acquisition methods like user interviews, application-specific
heuristics, and stereotypical inferences often are inflexible and
unsatisfying. In Information Retrieval, user models have been limited
to lists of terms relevant to an information need. The list is usually
very short for ad hoc querying and longer for information filtering
tasks.
Information systems that could benefit from having a user model should
be able to adapt to individual users, to learn about their preferences
and attitudes during the interaction (to construct a user profile),
and memorize them for later use. Moreover, these user profiles could
represent a starting point for the creation of user communities based
on shared interests or goals. Further, the system should be able to
update its model is a user changes interests.
Machine Learning (ML) is concerned with the formation of models from
observations. Hence, learning algorithms seem to be promising
candidates for user model acquisition systems.
Information Retrieval (IR) is concerned with the study of systems
for representing, organising, retrieving and delivering information
based on content.
User modeling is the glue. As the better we model users, the better
we can satisfy their information needs. We also aim to provide a forum
for researchers who are not necessarily familiar with the diverse
aspects of UM/ML/IR to be able to get acquainted with the
possibilities of collaboration between the communities. Thus, our
main goal is to build further bridges between three communities: User
Modeling, Machine Learning, and Information Retrieval.
We welcome your contributions to addressing these issues.
Our main goal is to build further bridges between three communities:
User Modeling, Machine Learning, and Information Retrieval.
------------------------------------------------------------------------
QUESTIONS TO BE ADDRESSED:
The two primary questions we would like to address are:
1. How can we apply Machine Learning and Information Retrieval
techniques to acquire and continuously adapt user models?
* What role can and should the user play in reviewing and
refining their own model?
* What are issues in modeling the user vs. modeling the
intermediary for IR?
* How can intelligent agents be used when in charge of
managing the interaction with an information system?
* How can we evaluate user-adaptive IR systems? Is it based on
effective retrieval, user experience, reaction and satisfaction?
* Where/How does the user fit into the picture? What kind of
user feedback is helpful/needed, and how can the user query/use the
learned model?
* How can ML be used for building user communities based on
common interests, and background? How do you apply IR techniques to
these?
* In the case of the description of a concrete application: Why
did you choose these particular techniques? How did they affect the
success of your application? What general conclusions can you draw
from your experiences?
2. SIG issues:
* What has been done since the last SIG meeting?
* How can SIG facilities be made more useful?
* What are possibilities for cooperation between SIG members?
* What could be activities the SIG should engage in?
* How can we get more people involved?
* What are the issues/problems that drive current research?
* What are the ways we can combine these three fields such that
changes in any field does not break the integrated system? Are there
any standards or good practices for integration that can be
identified
to address this issue at this stage?
------------------------------------------------------------------------
WORKSHOP FORMAT
The workshop program will be content-centered. Papers on related
topics will be grouped together into sessions, each of which will be
presented by a participant. Each session will have a small discussion
at the end to discuss issues related to that topic. General research
issues will be separated from SIG issues, which will be discussed at
the end of the workshop.
------------------------------------------------------------------------
SUBMISSIONS
Authors are required to submit papers not exceeding 10 pages as a PS
or PDF file. Each submission is required to address at least one of
the main workshop questions. Fulfillment of this requirement will be
assessed in the course of the review process.
Workshop papers will be published in full length in the workshop
proceedings and presented in talks at the workshop.
Submissions should be made to Ayse Goker <asga at scms.rgu.ac.uk>.
Authors are also requested to send and email to Ayse Goker
<asga at scms.rgu.ac.uk> containing the title of the paper,
the name of the file that has been submitted, the author name(s), the
author affiliation(s) and contact information.
Any queries regarding submission should be sent to: Ayse Goker,
(asga at scms.rgu.ac.uk) or Sofus A. Macskassy, (smacskas at stern.nyu.edu)
------------------------------------------------------------------------
IMPORTANT DATES
March 1: Submission deadline for Workshop papers
March 24: Notification of Workshop authors
April 3: Early Registration Deadline for the conference
April 15: Camera ready copies due
------------------------------------------------------------------------
ORGANIZERS
* Sofus A. Macskassy (smacskas at stern.nyu.edu)
Leonard N. Stern School of Business, NYU
* Ross Wilkinson (ross.wilkinson at csiro.au)
CSIRO
* Ayse Goker (asga at scms.rgu.ac.uk)
Robert Gordon University
* Mathias Bauer (bauer at dfki.de)
DFKI
-------------- next part --------------
A non-text attachment was scrubbed...
Name: -
Type: application/octet-stream
Size: 7767 bytes
Desc: not available
Url : http://mail.asis.org/pipermail/asis-l/attachments/20030122/51c231e9/attachment.obj
More information about the Asis-l
mailing list