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:
- Introduction/Overview of Data Mining and Getting to Know Your Data
- Data Pre-processing
- Classification: Basic Concepts – Decision Tree Induction
- Rule-Based Classification and Bayes Classification Methods
- Mining Frequent Patterns
- Associations
- Correlations and Cluster Analysis: Basic Concepts and Methods
- Outlier Detection
- Data Mining Trends and Research Frontiers
- Introduction of Text Mining
- Text mining Pre-Processing Technique
- Categorization, Clustering, and Information Extraction
- Text Mining Application
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