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[patterns-discussion] Call for Papers -- UDME 2007 @ OOPSLA 2007


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  • From: "M.E. Fayad" <mefayad AT gmail.com>
  • To: dacm-patterns AT cs.uiuc.edu, business-patterns AT cs.uiuc.edu, ipc-patterns AT cs.uiuc.edu, telecom-patterns AT cs.uiuc.edu, corba-patterns AT cs.uiuc.edu, gang-of-4-patterns AT cs.uiuc.edu, patterns-discussion AT cs.uiuc.edu, siemens-patterns AT cs.uiuc.edu
  • Subject: [patterns-discussion] Call for Papers -- UDME 2007 @ OOPSLA 2007
  • Date: Sat, 18 Aug 2007 05:18:21 -0700
  • List-archive: <http://lists.cs.uiuc.edu/pipermail/patterns-discussion>
  • List-id: General talk about software patterns <patterns-discussion.cs.uiuc.edu>

The First International Workshop on
Unified Data Mining Engine: Addressing Challenges

UDME 2007

Call for Papers

Montréal, Canada, October 22, 2007
(in conjunction with OOPSLA 2007)

http://www.oopsla.org/oopsla2007 (OOPSLA 2007 Link)
http://www.oopsla.org/oopsla2007/index.php?page=sub/&id=160 (Workshop Link 1)
http://www.engr.sjsu.edu/~fayad/workshops/UDME07 (Workshop Link 2)
http://www.vrlsoft.com/workshops/UDME07 (Workshop Link 3)

INTRODUCTION

Data mining is the discovery of knowledge of analyzing enormous set of
data, by extracting the meaning of the data and then predicting the
future trends. Data mining helps us to find out secret information
from large databases, and also helps companies to take sound
decisions, based on knowledge and information.

If we closely take a look into any data-mining tool, we can see there
are some common core logic, which are independent of the data and the
applications, but most of existing implementations try to ignore that
fact and concentrate on the specific problem, in that way the tool
becomes limited to only to a particular set of data for specific
application.

Data mining is also finding interesting patterns in data. The main
challenge of any data-mining engine is how to apply different
algorithms or different techniques, on different set of data, to find
interesting pattern, which is very useful to business. It is extremely
difficult to come with some standard way of analyzing the data. The
enormous volume and the complexity of the data make it impossible to
run same algorithms on different dataset. Nowadays, there are
different vendors, who are trying to solve this problem, but mostly
they support a subset of different algorithms. None of them has come
up with any stable engine, which can work in any data set and in any
domain.

In the last decade, the improvement in storage and CPU speed has
created a huge opportunity for different data mining application,
ranging from CRM to medical health care application. The evolution of
data mining is shown in table 1.

Now it is very difficult to develop a single application, which can
take care all of these problems. It's a dream even to think of an
application, which can iterate through any data and will find pattern.
Data mining also deals with useful pattern, not just patterns, now
whether a pattern is useful or not, depends on the context where it is
usually applied. Present day tools depend solely on the expert about
what kind of algorithms to apply, and how to analyze the output,
because most of them are generic, and there is no context specific
logic is attached to the application.

Here is s summary of the problems that we face today in the existing
data mining tools
1. Difficult to use– Existing data mining tools try to cover all
different data mining applications, thus it becomes very difficult to
configure and run.
2. Needs Expert to run the tool – No domain or problem specific
logic is tied with the tool, therefore needs expert to run the to tool
and analyze the result
3. Difficult to add new functionality - Because of the size and
complexity of each tool, it is very difficult to add any new feature.
4. Difficult to interface - There is no way those algorithms
developed by some other companies, can be integrated with the tool
easily
5. Short Lifetime - There is no stable component in the tool and
with time the tool become obsolete, as new tools take the market,
changing the exiting tool to incorporate new feature is difficult and
require lot of changes.
6. Limited Number of algorithms – Existing tool only provide
limited number of algorithm and sometime use of multiple algorithms is
very limited.
7. Need lot of resources: Existing tools are not optimized for any
specific application, therefore they need lot of resources, such as
runtime memory, hard disk etc.


Thus, this workshop is driven forward by three main questions. First,
"how can we develop a unified data mining engine {UDME)?" Second,
"what kind of technologies and tools to build such an Engine?" and
third, "how can we overcome the existing problems?"

OBJECTIVE AND MOTIVATION


Building such an engine is not an easy exercise, specifically, when
several factors can undermine their quality success, such as cost,
time, and lack of systematic approaches. We would like to architect
and develop a Unified Data Mining Engine (UDME), that has the some or
all of the following properties:
1. Ease of use– Multiple tools can be developed easily by focusing
on specific problems, because they all can share the core services,
that are provided by the UDME.
2. No Need of Expert to run the tool – Domain specific knowledge
such as verification, selection of tool etc, can be implemented in the
tool itself, while developing the tool.
3. Easy to add new functionality - – The application specific logic
should be separate from the core logic, therefore new application
specific functionality can be added easily, without making any change
in the core logic.
4. Easy to interface - The design should be based on system of
independent patterns, they can be developed by 3rd party vendors.
5. Long Lifetime - The engine should be based on stable core
logic, which has a long lifetime, the application logic should be
loosely connected which can change over time.
6. Multiple algorithms – The engine must support any number of algorithms.
7. Fewer resources: The proposed engine should be developed by
connecting several patterns or components. Depending on the
application, a domain the engine can use patterns or components,
which are necessary therefore it needs less resources compare to
existing tools.
8. Stable: The engine should be stable over time, and provide a
simple way to apply different data mining and data analysis algorithms
on different sets of data in any domain.
9. Isolation of Application logic: We must also isolate the stable
knowledge from any application specific logic, therefore different
applications can use the same core knowledge, which need not to be
changed.
10. Minimum Maintenance Cost – Maintenance cost of such an engine
should be very minimal.


WORKSHOP CHALLENGES

The workshop will address the unified data mining engine challenges
and debate several issues that are related to the following
questions. We also want researchers, framework developers, and
application developers to discuss and debate the following questions
related to:

I. UDME Architecture
a. What is the best approach for building such an engine?
b. What are the bases of creating the engine architecture?
c. Are there any guidelines, methodologies, and/or processes for an
engine architecture creation and development?
d. What are the components of the unified data mining engine architecture?
e. What kind of patterns or components that appear in UDME ?
f. Show how your engine architecture meets the above UDME properties.

II. UDME Development
a. What is the ultimate way to develop such an engine?
b. What are the techniques and tools for developing such an engine?
c. Show how to extend your engine to the new application logics?

More information will be available at:
http://www.oopsla.org/oopsla2007 (OOPSLA 2007 Link)
http://www.oopsla.org/oopsla2007/index.php?page=sub/&id=160 (Workshop Link 1)
http://www.engr.sjsu.edu/~fayad/workshops/UDME07 (Workshop Link 2)
http://www.vrlsoft.com/workshops/UDME07 (Workshop Link 3)

SUBMISSIONS

Developers and programmers, who are interested in participating in the
workshop, are requested to submit a short position paper (3-5 pages),
or regular workshop paper (limited to 6-15 pages, double spaced,
including figures) by representing views and experiences that are
relevant to the given discussion topic. The title page must include a
maximum 150-word abstract, five keywords, full mailing address, e-mail
address, phone number, fax number, and a designated contact author.
Workshop papers will be selected depending on their originality,
quality and relevance to the workshop. All submitted papers will also
be evaluated according to their originality, significance,
correctness, presentation and relevance. Papers should be submitted
electronically to the chair. Please follow the instructions that are
provided on the web page. Camera Ready manuscripts must be submitted
following ACM SIGPLAN conference proceedings style and guidelines. We
also encourage authors to present novel and fresh ideas, critiques of
existing work, and practical studies.

Each accepted workshop paper must be presented in the person, either
by the author or by one of the co-authors. To foster and promote
lively discussions, authors are encouraged to present open ended
questions and one or two main statements for the purpose of discussion
at the workshop. Submissions must be made either in MS-Word or RTF
formats (Please, DO NOT compress files).

Depending on the total number and spread of contributions, the scope
may be further narrowed down to ensure an effective communication and
information sharing session. Accepted position papers will be
distributed to the participants, just before the workshop and will be
made generally available through the WWW and FTP. Accepted papers
will also be published in the Workshop Proceedings. At least one of
the authors of each accepted paper must register, as a full delegate
in the workshop. Selected papers will be published in one of the
future issues of the online International Journal Of Patterns (IJOP),
www.ijop.org and/or International Journal of Software Architectures
(IJSA), www.ijsa.net

IPARTICIPATION

People who are interested in participating in the workshop, without
making any submissions are requested to fill out the participation
form and e-mail to any of the workshop chairs.
-------------------------------------------------
PARTICIPATION FORM:
Name and Affiliation:
Position:
Address:
E-mail:
URL:
Areas of interest:
Reasons for Attending?
-------------------------------------------------
Please note that registration is absolutely mandatory, in order to
participate in the workshop. An early registration discount is made
available for all desired participants. An overhead projector and a
flipchart will also be made available to all participants.

For more information please visit any of the following websites:

http://www.oopsla.org/oopsla2007 (OOPSLA 2007 Link)
http://www.oopsla.org/oopsla2007/index.php?page=sub/&id=160 (Workshop Link 1)
http://www.engr.sjsu.edu/~fayad/workshops/UDME07 (Workshop Link 2)
http://www.vrlsoft.com/workshops/UDME07 (Workshop Link 3)

You may also contact the organizers, either by e mail or by phone.

WORKSHOP AGENDA

1. Welcome and introduction of participants. The organizers will first
provide a short overview of all open issues, and also of the main
arguments arising out of the position papers. (Estimated time: 20-30
minutes)

2. Selected authors (who'll be representing the main trends) will be
allotted 20 minutes, to explain, how their position relates to other
positions, and what each one of them sees as the three major issues.
We are expecting about 5-10 position papers in this session.
(Estimated time: 120-130 minutes)

3. The organizers will also propose an identification process of the
major issues, and the participants will then discuss, choose and
select what they perceive are the hottest issues to be examined and
analyzed. (Estimated time: 10-15 minutes)

4. The participants will work for 70-95 minutes in small groups, with
a designated moderator assigned for leading each group. The groups
will then individually deal with two identified, but different hot
issues, and will produce a summary note in the form of points and
counterpoints, showing either how several views are irreducibly
opposed or how they are complementary. The total number of groups
will depend mainly on the number of participants and issues selected;
ideally there should be 3-5 people in each group. (Estimated time:
60-70 minutes)

5. Each group will be provided10-15 minutes to present its findings
and inferences to the workshop. A closing discussion will soon
follow. The workshop report will be composed on the basis of these
findings, and will include a clear cut agenda for future exploration
and cooperation; this will be made available through the WWW and FTP.
(Estimated time: 50-60 minutes for five teams)

(Total estimated time: 285-315 minutes, i.e. about five hours +/- 15
minutes; lunch and breaks are not included.)


IMPORTANT DATES

IMPORTANT DATES -- Will be updated based on acceptance process.

Submission deadline September 14, 2007
Acceptance notification September 30, 2007
Camera-ready paper due October 10, 2007
Workshop date: October 22, 2007
Conference begins: October 21, 2007

ORGANIZERS

DR. M.E. FAYAD (CHAIR)
Professor of Computer Engineering
Computer Engineering Dept., College of Engineering
San José State University
One Washington Square, San José, CA 95192-0180
Ph: (408) 924-7364, Fax: (408) 924-4153
E-mail:
m.fayad AT sjsu.edu,

mefayad AT gmail.com
http://www.engr.sjsu.edu/fayad

DR. TAREK HELMY (CO-CHAIR)
College of computer science and engineering,
Department of Information and Computer Science,
King Fahd University of Petroleum and Minerals,
Dhahran 31261, Mail Box. 413, Saudi Arabia.
Ph: 9663-860-1967 (Office)
E-mail:
helmy AT ccse.kfupm.edu.sa

DR. RAMI BAHSOON (CO-CHAIR)
School of Engineering and Applied Science
Aston University in Birmingham, Birmingham B4 7ET, United Kingdom
office: Main Building, Second Floor, MB 213E
Ph: +44 (0) 121 204 3464
fax: +44(0) 121 204 3681
URL: http://www-users.aston.ac.uk/~bahsoonr/index.htm

PROFESSOR DILIP PATEL (CO-CHAIR)
Faculty of Business, Computing and Information Management
London South Bank University
103 Borough Road
London SE1 0AA, United Kingdom
TEL: +44 (0)20 7815 7429

SOMENATH DAS (CO-CHAIR)
eBay, Inc.
2211 North First Street
San Jose, CA 95131, USA
Ph: 408 967 4151
E-mail:
sodas AT ebay.com

EDUARDO M. SEGURA (CO-CHAIR)
vrlSoft, Inc.
2065 Martin Ave., Suite 103
Santa Clara, CA 95050-2707
Phone/Fax: (408) 654-8972
E-mail:
esegura AT vrlsoft.com,

eduardo.segura AT sjsu.edu
http://www.vrlsoft.com

PROGRAM COMMITTEE

Rami Bahsoon, Aston University in Birmingham, United Kingdom
Rogerio Atem de Carvalho, Federal Center for Technological Education
of Campos, Brazil
Chia-Chu Chiang, University of Arkansas, Little Rock, USA
Issam Wajih Damaj, Dhofar University, Salalah, Sultanate of Oman
Somenath Das, eBay, Inc., USA
Dilip Patel, London South Bank University, United Kingdom
Jurgen Dix, Clausthal University of Technology, Germany
M.E. Fayad, San Jose State University and vrlSoft, Inc, Silicon Valley, USA
Jaafar Gaber, Université de Technologie de Belfort-Montbéliard, France
Rosario Girardi, Federal University of Maranhão, São Luís, Brasil
Dr. Tarek Helmy, King Fahd University of Petroleum and Minerals,
Dhahran, Saudi Arabia
Hoda Hosny, The American University in Cairo, Egypt
A. Kannammal, Coimbatore Institute of Technology, TamilNadu, India
Mohamed-Khireddine Kholladi, University of Constantine, France
Dae-Kyoo Kim, Oakland University, USA
Roger (Buzz) King, University of Colorado, Boulder CO, USA
Jianzhi Li, De Montfort University, United Kingdom
Nashat Mansour, Lebanese American University, Lebanon
Tokuro Matsuo, Yamagata University, Japan
Srini Ramaswamy, University of Arkansas, Little Rock, USA
Miguel Garre Rubio, Universidad de Alcalá, Madrid, Spain
Edaurdo M. Segura, San Jose State University and vrlSoft, Inc,
Silicon Valley, USA
Jaroslav Zendulka, Brno University of Technology, Czech Republic




  • [patterns-discussion] Call for Papers -- UDME 2007 @ OOPSLA 2007, M.E. Fayad, 08/18/2007

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