Machine Learning List: Vol. 17, No. 3
Tuesday, June 7, 2005
Contents
Calls for Papers/Participation
Utility-Based Data Mining workshop
EKDB&W EPIA-2005
SIGKDD-2005 Workshop on Link Discovery
AI*IA Workshop on Evolutionary Computation
IEEE ICDM'05
MRDM-2005
Open Source Data Mining Workshop
Miscellaneous Announcements
Stipend funding available for MSc Intelligent Systems
The Machine Learning List is moderated. Contributions should be
relevant to the scientific study of machine learning. Please send
submissions for distribution to: [EMAIL PROTECTED] For requests to be
added, removed, or to change your email address, send email to:
[EMAIL PROTECTED]
To keep mailings to a manageable size, please keep submissions brief.
For meeting announcements, do highlight the meeting Web site and the
goals of the event but omit information such as the program committee
and talk schedules. Also, only first calls for papers/participation
and brief change of deadline announcements will be included. The ML
List moderator reserves the right to omit/edit submissions to meet
these criteria.
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From: Maytal Saar-Tsechansky
Subject: Utility-Based Data Mining workshop
Date: Mon, 9 May 2005 01:47:45 -0500
Call for Papers
Utility-Based Data Mining Workshop
August 21, 2005
in conjunction with
The 11th ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining (KDD 2005)
August 21-24, 2005, Chicago, Illinois
Important Dates:
June 13, 2005: Deadline for electronic submission of full papers
June 30, 2005: Notification of accepted papers
July 15, 2005: Camera Ready Copies
Aug. 21, 2005: UBDM Workshop
The Utility-Based Data Mining workshop will address the impact of
economic utility on the various stages of the data mining process.
This includes methods and applications that adress the costs associated
with acquiring data, the costs of learning from the data, and the
costs and benefits of utilizing the learned knowledge. In addition to
work in cost-sensitive learning and active learning, the workshop aill
also address ideas for a comprehensive utility-based framework for the
data mining process.
The workshop will include invited talks, two panel discussions, paper
presentations, and short position papers.
For complete details please visit our workshop home page, at:
http://storm.cis.fordham.edu/~gweiss/ubdm-kdd05.html
------------------------------
From: Joao Gama <[EMAIL PROTECTED]>
Subject: EKDB&W EPIA-2005
Date: Mon, 09 May 2005 18:00:04 +0100
Second Call for Papers
EKDB&W 2005
Workshop on Extraction of Knowledge from Databases and Warehouses
Part of the 12th Portuguese Conference on Artificial Intelligence
Visit our Web site at http://centria.di.fct.unl.pt/conferences/ekdbw05/
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From: Jafar (Iman) Adibi <[EMAIL PROTECTED]>
Subject: SIGKDD-2005 Workshop on Link Discovery
Date: Mon, 09 May 2005 11:37:10 -0700
Call for Papers
Workshop on Link Discovery: Issues, Approaches and Applications
August 21, 2005, Chicago, IL, USA
To be held in conjunction with ACM SIGKDD-2005, 21-25 August 2005
Particular topics of interest for the workshop include but are not
limited to:
- Theoretical advances to link discovery and group detection
- Practical applications of link discovery to real world databases
- Link analysis and graph mining
- Social network analysis and community finding
- Graph theory, scale-free networks and small world phenomenon
- Web mining and text mining applied to link discovery
- Link discovery for data streams and scalability of developed approaches
- Record linkage, alias detection and object consolidation
- Visualization of link structures
- Performance evaluation measures
- Innovative applications in areas such as medical informatics, insurance,
laws enforcements and web communities
- Link discovery and other fields such as natural language processing,
agent theory, complex systems, trust models and dynamic pricing models
- Survey and analysis of deployed link discovery integrated systems,
commercial products, educational and commercial packages
IMPORTANT DATES
Submission Deadline: June 10, 2005
Acceptance Notification: July 7, 2005
Camera-ready Copies: July 15, 2005
Workshop date: August 21, 2005
For details please visit http://www.isi.edu/LinkKDD-05/
------------------------------
From: Stefano Cagnoni <[EMAIL PROTECTED]>
Subject: AI*IA Workshop on Evolutionary Computation
Date: Sat, 28 May 2005 20:31:40 +0200
AI*IA WORKSHOP ON EVOLUTIONARY COMPUTATION
A Satellite Workshop of the 9th Congress of
the Italian Association for Artificial Intelligence
University of Milan Bicocca
20 september 2005
http://AIIA2005.disco.unimib.it
CALL FOR PAPERS
Two types of contributions are solicited:
- Tutorials on different sub-topics and fields of application of
evolutionary computation
- Papers reporting original research results on topics which include,
but are not limited to:
- Evolutionary computation theory
- Real-world applications
- Comparison between results of evolutionary methods and the
state of the art in different application fields
- Hybrid evolutionary/non-evolutionary methods
Tutorial proposals must not exceed 4 A4 pages (single-column, single
spacing, 10 pt font size) and must be submitted by 20 June 2005. Papers
must not exceed 10 A4 pages, in Springer LNCS format or equivalent (see
www.springeronline.com/sgw/cda/frontpage/0,11855,5-164-2-72376-0,00.html)
and must be submitted by 27 June 2005.
Contributions must be in English and must be submitted by email, in
Postscript or pdf format, to the address [EMAIL PROTECTED] by the
proper deadlines. Accepted contributions will be published in the CD,
officially ISBN-catalogued, which will include the proceedings of all
satellite workshops of the Congress.
Important Dates
20 June 2005 Deadline for tutorial proposals
27 June 2005 Deadline for submission of papers
11 July 2005 Notification of acceptance
25 July 2005 Camera-ready papers due
20 September 2005 Workshop
21-23 September 2005 IX Congress of AI*IA
------------------------------
From: [EMAIL PROTECTED]
Subject: IEEE ICDM'05
Date: 2 Jun 2005 19:15:55 +0900
Final Call for Papers
ICDM '05: The 5th IEEE International Conference on Data Mining
Sponsored by the IEEE Computer Society
New Orleans, Louisiana, USA
27-30 November 2005
The 2005 IEEE International Conference on Data Mining (IEEE ICDM '05)
provides a premier forum for the dissemination of innovative, practical
development experiences as well as original research results in data
mining, spanning applications, algorithms, software and systems. The
conference draws researchers and application developers from a wide
range of data mining related areas such as statistics, machine learning,
pattern recognition, databases and data warehousing, data visualization,
knowledge-based systems and high performance computing. By promoting
high quality and novel research findings, and innovative solutions to
challenging data mining problems, the conference seeks to continuously
advance the state of the art in data mining. As an important part
of the conference, the workshops program will focus on new research
challenges and initiatives, and the tutorials program will cover
emerging technologies and the latest developments in data mining.
Topics of Interest
Topics related to the design, analysis and implementation of data mining
theory, systems and applications are of interest. These include, but
are not limited to the following areas:
* Foundations of data mining
* Data mining and learning methods for classification, regression,
clustering, probabilistic modeling, and association analysis
* Mining text, semi-structured, temporal, spatial, and multimedia data
* Mining data streams
* Pattern recognition and trend analysis
* Collaborative filtering/personalization
* Data and knowledge representation for data mining
* Query languages and user interfaces for mining
* Complexity, efficiency, and scalability issues in data mining
* Data pre-processing, data reduction, feature selection/transformation
* Post-processing of data mining results
* Statistics and probability in large-scale data mining
* Neural networks, fuzzy logic, evolutionary computation, rough sets,
and uncertainty management for data mining
* Integration of data warehousing, OLAP and data mining
* Human-machine interaction and visual data mining
* High performance and parallel/distributed data mining
* Quality assessment and interestingness metrics of data mining results
* Security, privacy and social impact of data mining
* Applications in bioinformatics, electronic commerce, Web, intrusion
detection, finance, marketing, healthcare, and telecommunications
Important Dates
June 15, 2005 Paper submissions
Tutorial proposals
Workshop proposals
Panel proposals
August 20, 2005 Paper acceptance notices
September 7, 2005 Final camera-readies
November 27, 2005 Tutorials and Workshops
November 28-30, 2005 Conference
All paper submissions will be handled electronically. Detailed
instructions are provided on the conference home page at
http://www.cacs.louisiana.edu/~icdm05
---------------------------------
From: Saso Dzeroski <[EMAIL PROTECTED]>
Subject: MRDM-2005
Date: Fri, 03 Jun 2005 15:17:50 +0200
FINAL CALL FOR PAPERS
MRDM 2005 - 4th Workshop on Multi-Relational Data Mining
organised at the
11th ACM SIGKDD International Conference
on Knowledge Discovery & Data Mining
August 21 - 24, 2005, Chicago, IL, USA
Paper submissions due: June 10, 2005
Workshop Website: http://www-ai.ijs.si/SasoDzeroski/MRDM2005/
Workshop Contact: Saso Dzeroski <[EMAIL PROTECTED]>
Workshop Date: August 21, 2005
Workshop chairs: Saso Dzeroski <[EMAIL PROTECTED]>,
Hendrik Blockeel <[EMAIL PROTECTED]>
Multi-Relational Data Mining (MRDM) is the multi-disciplinary field
dealing with knowledge discovery from relational databases consisting
of multiple tables. Mining data which consists of complex/structured
objects also falls within the scope of this field, since the normalized
representation of such objects in a relational database requires multiple
tables. The field aims at integrating results from existing fields such
as inductive logic programming, KDD, machine learning and relational
databases; producing new techniques for mining multi-relational data;
and practical applications of such techniques.
TOPICS OF INTEREST
The topics of interest (listed in alphabetical order) include,
but are not limited to, the following:
- Applications of (multi-)relational data mining
- Data mining problems that require (multi-)relational methods
- Distance-based methods for structured/relational data
- Inductive databases
- Kernel methods for structured/relational data
- Learning in probabilistic relational representations
- Link analysis and discovery
- Methods for (multi-)relational data mining
- Mining structured data, such as amino-acid sequences, chemical
compounds, and HTML or XML documents
- Mining relational data from continuous streams
- Propositionalization methods for transforming (multi-)relational
data mining problems to single-table data mining problems
- Relational neural networks
- Relational pattern languages
- Statistical relational learning
We also encourage submissions which present early stages of research
work, software, and applications.
----------------------------
From: Bart Goethals <[EMAIL PROTECTED]>
Subject: Open Source Data Mining Workshop at SIGKDD 2005
Date: Thu, 02 Jun 2005 13:36:39 +0200
OSDM 2005: Open Source Data Mining Workshop
In conjunction with ACM SIGKDD 2005
Chicago, Illinois, USA
August 21st, 2005
Over the past decade tremendous progress has been made in data mining
methods like clustering, classification, and frequent pattern mining.
However, the advanced implementations are often not made publicly
available, and thus the results cannot be independently verified. This
hampers rapid advances in the field. There is thus a critical need to
have open source implementations of important data mining methods.
This workshop is the first such meeting place to discuss open source
data mining methods. We will focus our attention in the first year to
frequent pattern mining problems. In subsequent years we will focus
on open source implementations for other data mining problems like
clustering, classification, and outlier detection.
Frequent pattern mining is a core field of research in data mining
encompassing the discovery of patterns such as itemsets, sequences,
trees, and graphs. Generally speaking, the problem involves the
identification of items, products, symptoms, characteristics, and so
forth, that often occur together in a given data set. As a fundamental
operation in data mining, algorithms this task can be used as a
building block for other, more sophisticated data mining approaches.
During the last decade, a huge number of algorithms have been
developed to efficiently solve such problems.
Submissions consist of source code in addition to a paper that describes
the implemented algorithm and provides a performance study on publicly
provided data sets. We request that the paper also provides a deep
analysis of the proposed techniques, by presenting results on the
performance of the algorithm with and without each of the used
techniques or optimizations, and, if appropriate, an explanation of
why the algorithm performs better than existing implementations or
algorithms. The submitted source code will become part of an open
source data mining repository that will be widely publicised.
The workshop participants will be invited to discuss the submission;
there will be a heavy focus on critical evaluation, i.e., what are the
limitations, under what conditions does the algorithm work well, why
it fails in other cases, and what are the open areas. One outcome will
be to outline the focus for research on new problems in the field.
Although there will be no performance contest, we believe that the
open source nature of the workshop encourages authors to accurately
and honestly compare their algorithms with others, and vice versa.
More detailed submission information can be found on the website of the
workshop: http://osdm.ua.ac.be/
Important dates
Submission Deadline: June 8, 2005
Notification: July 8, 2005
Camera-ready Copies: July 18, 2005
Workshop date: August 21, 2005
Workshop co-chairs
Bart Goethals, University of Antwerp, Belgium
Siegfried Nijssen, University of Leiden, The Netherlands
Mohammed Zaki, Rensselaer Polytechnic Institute, USA
To disseminate the workshop results widely, the proceedings will be
published online in the ACM Digital Library.
----------------------------
From: Stefan Wermter <[EMAIL PROTECTED]>
Subject: Stipend funding available for MSc Intelligent Systems
Date: Wed, 25 May 2005 17:30:02 +0100
Stipends available for MSc Intelligent Systems
We are pleased to announce that for eligible EU students we have
obtained funding to offer a bursary for our MSc Intelligent Systems
in October 2005 of about 8.000 EURO as fee waiver and stipend.
The School of Computing and Technology, University of Sunderland is
delighted to announce the launch of its MSc Intelligent Systems
programme for October 2005. Building on the School's leading edge
research in intelligent systems this masters programme will be funded
via the ESF scheme (see below).
Intelligent Systems is an exciting field of study for science and
industry since the currently existing computing systems have often not
yet reached the various aspects of human performance. "Intelligent
Systems" is a term to describe software systems and methods that
simulate aspects of intelligent behaviour. The intention is to learn
from nature and human performance in order to build more powerful
computing systems. The aim is to learn from cognitive science,
neuroscience, biology, engineering, and linguistics for building more
powerful computational system architectures. In this programme a wide
variety of novel and exciting techniques will be taught including
neural networks, intelligent robotics, machine learning, natural
language processing, vision, evolutionary genetic computing, data
mining, fuzzy methods, and hybrid intelligent architectures.
The Bursary Scheme applies to this Masters programme commencing
October 2005 and we have obtained funding through the European Social
Fund (ESF). ESF support enables the University to waive the normal
tuition fee and provide a bursary for 45 weeks to eligible EU students.
For further information in the first instance please see:
http://www.his.sunderland.ac.uk/Teaching_frame.html
http://www.his.sunderland.ac.uk/teaching/sund_is_app.pdf
For information on applications and start dates contact:
[EMAIL PROTECTED] Tel: 0191 515 2758
For academic information about the programme contact:
[EMAIL PROTECTED]
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End of ML-LIST Digest Vol 17, No. 3
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