Câu 46: UiASAPv1: UiPath Automation Solution Architect Professional v1.0

What is the difference between rule-based and model-based data extraction methodologies?

1. A. Rule-based extraction is more computationally intensive, whereas model-based systems are simpler and require fewer computational resources.
2. B. Rule-based extraction requires manual data labeling, while model-based extraction does not need any label or training data.
3. C. Rule-based extraction relies on predefined rules and patterns, while model-based extraction utilizes machine learning algorithms to automatically identity and extract data. — đáp án hiện tại
4. D. Model-based extraction is only effective for structured data sources, whereas rule-based extraction can handle both structured and unstructured data sources seamlessly.