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Log anomaly detection 저자: Mind Map: Log anomaly detection

1. Literature Map

2. Applications

3. Approaches

3.1. Supervised Learnign

3.2. Unsupervised Learning

3.3. Semi-Supervised Learning

4. Different Types of log data

4.1. System Logs

4.2. Network Logs

4.3. Application Logs

4.4. Cloud Logs

4.5. Security Logs

5. Datasets

6. Data Preprocessing

6.1. Log Parsing

6.2. Data Cleaning

6.3. Feature Extraction

6.4. Dimentionaly Reduction

6.5. Normalization and Scaling

7. Algorithms

7.1. Machine Learning Models

7.2. Deep Learning Models

8. Evaluation Metrics