People Innovation Excellence

Data and Text Mining (4 Credits)

Learning Outcomes:

Explain the basic concepts of data mining and text mining techniques; Analyze collection of data, text, and techniques for pre-processing the data and text before mining; Analyze case studies and design mining techniques to solve problems by extracting knowledge from data and text; Analyze trends and application related to data and text mining

Topics:

  1. Introduction/Overview of Data Mining and Getting to Know Your Data
  2. Data Pre-processing
  3. Classification: Basic Concepts – Decision Tree Induction
  4. Rule-Based Classification and Bayes Classification Methods
  5. Mining Frequent Patterns
  6. Associations
  7. Correlations and Cluster Analysis: Basic Concepts and Methods
  8. Outlier Detection
  9. Data Mining Trends and Research Frontiers
  10. Introduction of Text Mining
  11. Text mining Pre-Processing Technique
  12. Categorization, Clustering, and Information Extraction
  13. Text Mining Application

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