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The 6th International Conference on Discovery Science

DS 2003

Submission Page


To revise a previous submission, please type in its passcode below, and press the ENTER button.

   

If you lost the passcode for your submission, please click HERE.


To make a new submission, please fill in the form below, and then press the submit button at the bottom.


Title of Submission:  


List of Authors:

Please enter the complete list of authors for your submission, in the order in which they will appear on the abstract. You can add as many author slots as you want, to accommodate the total number of authors for your submission.

First name(s) Last name Email Affiliation
#1
#2
#3
#4
#5
#6
#7
#8
#9
#10
#11
#12
#13
#14
#15
#16
#17
#18
#19
#20

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Contact Informaton:

Title 
First name*
Last name*
  Affiliation/organization*
       Affiliation Dept/Lab 
Phone*
Fax 
Email*
Country*
Address 
Address 
Address 
City/Town*
Zip/Postal Code*


Submission Categories:

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Submission type:  
Programm Committee:  


Summary:

Type (or cut-and-paste) a short summary for your submission. You must enter plain text only.

 


Submit Paper:

Your submission must be in one of the following document formats:

  • Adobe PDF (pdf)
  • Postscript (ps)

The file's name should have the proper MIME extent associated with its document type. For example, a pdf file could have a name such as "mypaper.pdf".

Find the file containing your submission: 


Keywords/Topics:

Please use the list of topics below to characterize your submission. Check all categories that seem appropriate.

Logic for/of knowledge discovery
Knowledge discovery by inferences
Abductive reasoning
Heuristic search
Constructive programming as discovery;
Knowledge discovery from texts and the Web
Knowledge discovery from unstructured and multimedia data
Knowledge discovery in databases
Data mining
Data and knowledge visualization
Active mining
Knowledge discovery in network environments; Intelligent network agents
Statistical methods and neural networks
Bayesian learning
Machine learning (other technique than bayesian, statistical and neural networks)
Meta-learning, combining machine learning algorithms
Knowledge discovery and human interaction
Human factors in knowledge discovery
Philosophy and psychology of discovery
Chance discovery, Scientific discovery
Application of knowledge discovery to other sciences (e.g. natural and social sciences)
 
 



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