Text Analytics with RapidMiner Part 1 of 6 - Loading Text

Published on 11/8/2010

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I’ll be releasing a new video on text mining with RapidMiner every day this week.

They’re all about 10 minutes long, and go into a fair amount of detail, and should be easy to understand. Your feedback is appreciated!

Here is the first one. It’s about loading text into RapidMiner in a variety of ways. From copy and paste, to HTML files, to database reads.

*NOTE: You may need to use the Nominal To Text operator to turn your text field into a field that RapidMiner understands as “text”. It’s under Data Transformation, Type Conversion.

Later this week:

Tuesday: Processing Text in RapidMiner - tokenizing, stripping HTML, stemming, stopwords, n-grams, and word frequency tables.

Wednesday: Association rules with text in RapidMiner - making word vectors, finding frequent item-sets and high-confidence association rules in text documents.

Thursday: Finding similar documents: how to automatically calculate the similarity between documents. TF-IDF, cosine similarity and K-Means clustering are covered.

Friday: Automatic classification: How to classify documents into classes (like positive/negative reviews, or spam/not spam or sports/finance/leisure news), and which words are important.

NEW: Applying A Model To New Documents

Hope you enjoy them.

See my other data mining videos here

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