The course "Web Mining and Web Usage with RapidMiner" is an introduction into web mining and web analytcis. It covers topics like web crawlers, automated web page classification and clustering, information extraction from web pages, personalized news agents, web log file analysis and mining as well as web site or web shop optimization. In combination with a recommendation engine this can even include automated personalized product recommendations which allow for Up-Selling and Cross-Selling in order to achieve higher sales volumes. You will learn how to connect RapidMiner with a web crawler, how to automatically collect and process web pages, how to train web page or blog entry classifiers for content-based, user-preference-based, or sentiment-based document categorizations, how to automatically extract information from web pages using XPath and regular expressions. The course will also show how to integrate web services like the Amazon API, e.g. for extracting product information, or the Google API, e.g. for extracting geographical information. Many practical exercises for different settings like adaptive personal news filtering or sentiment analysis of text documents like web pages, news, blogs, discussion groups or PDF documents will enable the participants to transfer the gained knowledge to own web mining problems.

You can register to this course online.

Details

• Course ID: 180802
• Date: June 26th - 27th, 2008
• Number of days: 2 days
• Location: Dortmund, Germany
• Target audience: decision makers, data mining users, analysts, developers, administrators
• Previous knowledge: basic knowledge of computer programs
• Methods: lectures, discussions, individual and group work, exercises on realistic data. Participants may introduce own work and project specific questions in order to find particular solutions together with the trainer and other participants.
• Content: this course includes a compact introduction into the foundations of data mining and into the software RapidMiner. It addresses beginners and intermediate learners. Topics of this course are
  • Basics of Data Mining with RapidMiner
  • Introduction into Data Mining on the web and on texts
  • Connecting a web crawler to RapidMiner
  • Preprocessing of textual data: tokenizing, tagging, term frequencies, document frequencies, TFIDF
  • Machine Learning methods for text mining: Naive Bayes and Support Vector Machines
  • Automatic text classification: classifying web pages or blogs or discussion entries according to content, user-preferences, or sentiments
  • Text clustering: automatically clustering web pages or other texts into groups of similar documents
  • Information extraction using XPath or regular expressions
  • Integrating the Amazon API and the Google API
  • Web log analysis and mining
  • Providing personalized product recommendations
  Extensive exercises on different data sets will be performed.

Prices

Value added tax (VAT) may have to be added to these base prices.