Overview of Text Mining and NLP Techniques

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Processing and analysis of the unstructured text is a very useful part of any data scientist’s toolkit - but if you’ve never tried it before, it can be intimidating. Have you ever wondered how to classify the sentiment of product reviews or extract topics from a large set of documents in an automated way?

If you’ve wanted to try using the text processing features available in the KNIME Analytics Platform, but just didn’t know where to begin, this session is for you. And since we’ll be using KNIME, you’ll see how easy this process can be using a no-code approach, and you’ll take with you example workflows to explore further on your own via the KNIME Hub.

Come join Scott and Lisa for a jumpstart session, where we’ll cover:

● A brief introduction to text processing philosophy
● Important nodes in the Text Processing extension
● A sentiment analysis example using movie reviews
● A topic extraction example using medical abstracts
● A live data app example using real-time tweets

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Table of Contents:
00:00 Introduction
00:42 Agenda
01:29 KNIME Analytics Platform- Visual KNIME Workflows
03:21 Philosophy of Text Mining
06:08 Additional Data Types
07:54 Sentiment Analysis
15:35 Sentiment Analysis Demo
26:20 Clustering and LDA
49:17 Resources/ Wrap-up
51:35 Q&A

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#naturallanguageprocessing

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