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MM - Write short notes on ASM.

Certainly! Here are the key concepts and short sentences that you can use to create a mind map for Association Rule Mining (ASM):

Association Rule Mining (ASM) Mind Map

1. Introduction

  • Definition: Finding relationships in data
  • Purpose: Discover patterns & associations

2. Objective

  • Identify strong rules in databases
  • Market basket analysis
  • Cross-selling strategies
  • Recommendation systems

3. Terminology

  • Itemset: Collection of items
    • Frequent Itemset: Appears frequently
  • Support: Proportion of transactions with itemset
    • ( \text{Support}(A) = \frac{\text{Transactions with } A}{\text{Total transactions}} )
  • Confidence: Likelihood of item B with A
    • ( \text{Confidence}(A \rightarrow B) = \frac{\text{Support}(A \cup B)}{\text{Support}(A)} )
  • Lift: Association strength over random
    • ( \text{Lift}(A \rightarrow B) = \frac{\text{Confidence}(A \rightarrow B)}{\text{Support}(B)} )

4. Key Algorithms

  • Apriori Algorithm
    • Steps: Generate frequent itemsets, create rules
    • Example: {Milk, Bread} frequent, {Milk} → {Bread}
  • FP-Growth Algorithm
    • Steps: Construct FP-tree, extract frequent itemsets
    • Example: FP-tree compression, recursive extraction

5. Applications

  • Market Basket Analysis
    • Analyze purchase data
    • Example: Bread & butter association
  • Recommendation Systems
    • Suggest products/services
    • Example: E-commerce recommendations
  • Web Usage Mining
    • Analyze web logs
    • Example: Common navigation paths
  • Intrusion Detection
    • Detect abnormal patterns
    • Example: Network security threats

6. Advantages

  • Uncover hidden patterns
  • Applicable to various domains
  • Actionable business insights

7. Challenges

  • Scalability: Handling large datasets
  • Relevance: Filtering useful rules
  • Complexity: Computational challenges

Example Mind Map Layout

  1. Center Node: Association Rule Mining (ASM)

  2. Branches:

    • Introduction
      • Definition
      • Purpose
    • Objective
      • Identify rules
      • Market analysis
      • Cross-selling
      • Recommendations
    • Terminology
      • Itemset
        • Frequent Itemset
      • Support
        • Formula
      • Confidence
        • Formula
      • Lift
        • Formula
    • Key Algorithms
      • Apriori Algorithm
        • Steps
        • Example
      • FP-Growth Algorithm
        • Steps
        • Example
    • Applications
      • Market Basket
        • Example
      • Recommendations
        • Example
      • Web Mining
        • Example
      • Intrusion Detection
        • Example
    • Advantages
      • Hidden patterns
      • Multiple domains
      • Business insights
    • Challenges
      • Scalability
      • Relevance
      • Complexity

By organizing these keywords and short sentences into a mind map, you can visually capture and recall the essential concepts and relationships within Association Rule Mining.