CFP: First International Workshop on Knowledge Discovery in Data Streams

jgama jgama at liacc.up.pt
Wed Jun 9 03:11:41 EST 2004


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2nd Announcement & Call for Papers

First International Workshop on Knowledge Discovery in Data Streams
24 September 2004, Pisa, Italy

http://www.lsi.us.es/~aguilar/ecml2004/

Submission deadline: June 14, 2004
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in conjunction with ECML/PKDD 2004: 
The 15th European Conference on Machine Learning (ECML) and 
The 8th European Conference on Principles and Practice of Knowledge
Discovery in Databases (PKDD), 
http://ecmlpkdd.isti.cnr.it/

MOTIVATION
Databases are growing incessantly and many sources produce data
continuously. In many cases, we need to extract some sort of knowledge
from this continuous stream of data. Examples include customer click
streams, telephone records, large sets of web pages, multimedia data,
scientific data, and sets of retail chain transactions. These sources
are called data streams. The goal of this workshop is to convene
researchers who deal with decision rules, decision trees, association
rules, clustering, filtering, preprocessing, post processing, feature
selection, visualization techniques, etc. from data streams and related
themes. We are looking for all possible contributions related to
inductive learning from data streams.


The goal of this workshop is to convene researchers who deal with
decision rules, decision trees, association rules, clustering,
filtering,preprocessing, post processing, feature selection,
visualization techniques, etc. from data streams and related themes.

Research works presenting theoretical results, basic research,
perspective solutions and practical developments are welcome, provided
that they address the topic of the workshop. Position papers are also
welcome and encouraged.

Topics of Interest
Topics include (but are not restricted to):

    * Data Stream Models
    * Clustering from Data Streams
    * Decision Trees from Data Streams
    * Association Rules from Data Streams
    * Decision Rules from Data Streams
    * Feature Selection from Data Streams
    * Visualization Techniques for Data Streams
    * Incremental on-line Learning Algorithms
    * Mining spatio-temporal data streams
    * Scalable Algorithms
    * Real-Time Applications
    * Real-World Applications

Important Dates

      Submission deadline: June 14, 2004
      Notification of acceptance: July 5, 2004
      Camera-ready copies due: July 12, 2004



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