In process mining, three core activities are Process Discovery, Conformance Checking, and Process Enhancement.

1. **Process Discovery**: Also known as process model generation, this activity involves extracting a process model from a dataset of event logs collected from an information system. The goal is to discover the underlying process structure and behavior. There are two types of process discovery: Automatic and Interactive. Automatic discovery creates a model based on algorithms such as alpha-algorithm, ILP (Inductive Logic Programming), and heuristic miner. Interactive discovery presents a set of candidate models to the user who has to select the most accurate one.
2. **Conformance Checking**: This activity compares a discovered process model with a set of event logs collected from an actual system. It measures the likelihood of an actual execution adhering to a predefined process model, which is often used to identify deviations and misbehavior in the process. Conformance Checking can be used to assess how accurately a process model represents the actual process.
3. **Process Enhancement**: Process enhancement, also known as process improvement, is a broader field that encompasses multiple problem-solving approaches to design more efficient, effective, and optimizes business processes. While discovery and conformance checking provide insight into available process patterns, this phase gets applied knowledge of business goals, costs, and market dynamics to propel those processes toward even greater synergy. The purpose of process enhancement is to enhance or modify the process to make it more efficient, reduce costs, improve quality, and innovate process capabilities.