Mining Different Kinds of Knowledge
Characterization: Generalize, summarize, and possibly contrast data characteristics, e.g., dry vs. wet regions.
Association: Rules like “inside(x, city) à near(x, highway)”.
Classification: Classify data based on the values in a classifying attribute, e.g., classify countries based on climate.
Clustering: Cluster data to form new classes, e.g., cluster houses to find distribution patterns.
Trend and deviation analysis: Find and characterize evolution trend, sequential patterns, similar sequences, and deviation data, e.g., housing market analysis.
Pattern-directed analysis: Find and characterize user-specified patterns in large databases, e.g., volcanos on Mars.