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    SUMMER SCHOOL 2010 - 8-th SUMMER SCHOOL ON DATA MINING

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    Website www.cs.unimaas.nl/datamining/ | Want to Edit it Edit Freely

    Category SUMMER SCHOOL 2010

    Deadline: August 27, 2010 | Date: August 30, 2010-September 02, 2010

    Venue/Country: Maastricht, Netherlands

    Updated: 2010-08-10 00:36:23 (GMT+9)

    Call For Papers - CFP

    ** **

    ** 8-th SUMMER SCHOOL ON DATA MINING, Maastricht, The Netherlands **

    ** http://www.cs.unimaas.nl/datamining/ **

    ** **

    ** Apologies if you receive multiple copies of this announcement **

    ** Please forward to anyone who might be interested **

    ** **

    Summer School: Data Mining

    An intensive 4-day introduction to methods and applications

    Department of Knowledge Engineering, Maastricht University,

    Maastricht, The Netherlands

    August 30 - September 2, 2010

    Introduction

    Most business organizations collect terabytes of data about business

    processes and resources. Usually these data provide just "facts and

    figures", not knowledge that can be used to understand and eventually

    re-engineer business processes and resources. Scientific community in

    academia and business have addressed this problem in the last 20 years

    by developing a new applied field of study known as data mining.

    In practice data mining is a process of extracting implicit,

    previously unknown, and potentially useful knowledge from data. It

    employs techniques from statistics, artificial intelligence, and

    computer science. Data mining has been successfully applied for

    acquiring new knowledge in many domains (like Business, Medicine,

    Biology, Economics, Military, etc.). As a result most business

    organizations need urgently data-mining specialists, and this is

    the point where this school comes to help.

    Description

    The school curicullum is well balanced between theory and practice.

    Each lecture is accompanied by a lab in which participants experiment

    with the techniques introduced in the lecture. The lab tool is Weka, one

    of the most advanced data-mining environments. A number of real data

    sets will be analysed and discussed. In the end of the school

    participants develop their own ability to apply data-mining techniques

    for business and research purposes.

    Tools

    The school focuses on techniques with a direct practical use.

    A step-by-step introduction to powerful (freeware) data-mining tools

    will enable you to achieve specific skills, autonomy and hands-on

    experience. A number of real data sets will be analysed and discussed.

    In the end of the school you will have your own ability to apply data-

    mining techniques for research purposes and business purposes.

    Content

    The school will cover the topics listed below.

    - The Knowledge Discovery Process

    - Data Preparation

    - Basic Techniques for Data Mining:

    + Decision-Tree Induction

    + Rule Induction

    + Instance-Based Learning

    + Bayesian Learning

    + Support Vector Machines

    + Regression Techniques

    + Clustering Techniques

    + Association Rules

    - Tools for Data Mining

    - How to Interpret and Evaluate Data-Mining Results

    Intended Audience

    This school is intended for four groups of data-mining beginners:

    students, scientists, engineers and experts in specific fields who need

    to apply data-mining techniques to their scientific research, business

    management, or other related applications.

    SIKS

    Participating in this school is a part of the advanced components stage

    of SIKS' educational program. SIKS has reserved a number of places for

    those Ph.D-students working on the school topics.

    Prerequisites

    The school does not require any background in databases, statistics,

    artificial intelligence, or machine learning. A general background in

    science is sufficient as is a high degree of enthusiasm for new

    scientific approaches.

    Certificate

    Upon request a certificate of full participation will be provided after

    the school.

    Registration

    To register for the school please send an email to the registration office

    specifying the following information:

    - Name

    - University / Organisation

    - Address

    - Phone

    -E-Mail

    Please register before August 27, 2010

    Registration fees

    Academic fee 600 Euros

    Non-academic fee 850 Euros

    Included in the price are: school material and coffee breaks. The local

    cafeteria will be available for lunch (not included).

    SIKS-Ph.D. students

    Participating in this school is a part of the advanced components stage

    of SIKS' educational program. SIKS has reserved a number of places for

    those Ph.D-students working on the school topics. SIKS-Ph.D.-students

    interested in taking the school should NOT contact the local organization,

    but send an e-mail to officeatsiks.nl and confirm that their supervisor

    supports their participation

    E-mail should be sent to: smirnovatmaastrichtuniversity.nl

    Regular mail should be sent to:

    Evgueni Smirnov

    Department of Knowledge Engineering

    Faculty of Humanities and Sciences

    Maastricht University

    P.O.Box 616

    6200 MD Maastricht

    The Netherlands

    Phone: +31 (0) 43 38 82023

    Fax: +31 (0) 43 38 84897


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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