2.txt

This complete matlab for neural network

发信人: roamingo (漫步鸥), 信区: DataMining
标  题: Update notification: WUM 7.0 Beta (Demo)
发信站: 南京大学小百合站 (Tue Nov 20 09:58:35 2001), 站内信件

WUM - A Web Usage Mining Tool written in Java.

       ---- A notification Email ----

Dear user,

thank you for your interest in the Web Utilization Miner WUM that
is being developed at the Humboldt University Berlin, Germany and 
at the Leipzig Graduate School of Management (HHL). You registered to 
download one of the previous beta versions. We are glad to announce 
that the new demo version 7.0 Beta is now available for download at 
the WUM Web site. Brief information about the new version and a screenshot
can be found at http://ebusiness.hhl.de/research/wum/index_en.php

Due to extensive use of the Java Collection API, WUM 7.0 Beta 
requires Java 2 formally known as JDK 1.2.2 or higher. Please download 
one of the following archives

- http://wum.wiwi.hu-berlin.de/download2/WUM.v70.tar.gz
  (1489737 Bytes)

- http://wum.wiwi.hu-berlin.de/download2/WUM.v70.zip
  (1494921 Bytes)

within the next week. After that period of time, these files will be 
removed due to space limitations. Both archives have the same content.
It's strongly recommended to install the miner on a system with at least 
128 MB memory. There's a concise description of the installation process 
and the license in the archive to be downloaded or at our Web site:

- http://wum.wiwi.hu-berlin.de/download/WUM.installation.txt
- http://wum.wiwi.hu-berlin.de/download/WUM.copyright.txt

If you have any questions or suggestions regarding WUM, please do 
not hesitate to contact Myra Spiliopoulou ([e-mail])
or me ([e-mail]). 

Please remember that this code is a demo prototype intended for 
research purposes only. The WUM team would appreciate any bug 
reports or feature suggestions concerning the future development
of the miner. Please visit http://wum.wiwi.hu-berlin/bugs! 


Kind regards,
Karsten
---
Karsten Winkler
Department of E-Business
Leipzig Graduate School of Management (HHL)
http://ebusiness.hhl.de/staff/kwinkler

--
Read digitally, save a tree.

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