Text Analytics Using SAS Text Miner

This course describes the functionality of SAS Text Miner software, which is a separately licensed component that is available for SAS Enterprise Miner.

Duration 2 Days
Certificate SAS Global
Language English

Fees 1600

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About Program

This course describes the functionality of SAS Text Miner software, which is a separately licensed component that is available for SAS Enterprise Miner. In this course, you learn to use SAS Text Miner to uncover underlying themes or concepts contained in large document collections, automatically group documents into topical clusters, classify documents into predefined categories, and integrate text data with structured data to enrich predictive modeling endeavors.

This course can help prepare you for the following certification exam(s): SAS Text Analytics, Time Series, Experimentation and Optimization.

Format of Training

Taught by certified instructors at high-tech facilities across the country

All the benefits of the classroom without the travel

  • Join the classroom right from your desktop
  • Led by an expert instructor who can virtually look over your shoulder
  • Ask questions and get answers in real-time
  • Access the latest software via a virtual lab
  • Receive 20 business days' access to a recording of your course
  • Discuss, share, exchange ideas with participants from different countries

Training Features

  • convert documents stored in standard formats (Microsoft Word, Adobe PDF, and so on) into general purpose HTML or TXT formats
  • read documents from a variety of sources (web pages, flat files, data elements in a relational database, spreadsheet cells, and so on) into SAS tables
  • process textual data for text mining (for example, correct misspellings or recode acronyms and abbreviations)
  • convert unstructured text-based character data into structured numeric data
  • explore words and phrases in a document collection
  • query document collections using keywords (that is, identify documents having specific words or phrases)
  • identify topics or concepts that appear in a document collection
  • create user-influenced topic tables from scratch or by modifying machine generated topics or concepts using domain knowledge
  • use derived topic tables or pre-existing user-influenced topic tables (or both) to enhance information retrieval and document classification
  • cluster documents into homogeneous subgroups
  • classify documents into predefined categories.

Course Curriculum

Introduction to SAS Enterprise Miner and SAS Text Miner

  • data mining and text mining
  • working with data sources
  • using SAS Enterprise Miner and SAS Text Miner

Overview of Text Analytics

  • using the Text Import node, adding a target variable, and comparing models
  • a forensic linguistics application
  • information retrieval
  • text categorization

Algorithmic and Methodological Considerations in Text Mining

  • methods for parsing and quantifying text
  • dimension reduction with SVD

Additional Ideas and Nodes

  • some predictive modeling details
  • Text Profile node
  • High Performance (HP) Text Miner node

Course Fees





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