In recent years, command-line interface (CLI) commands have become more articulated and increased in complexity. This has underscored the possible need for advanced tools that can efficiently analyze and understand this data. In this thesis, Bash is the language taken into account. Command-line interactions, which are integral to system administration, software development, and data processing, often involve sequences of commands, from now on called sessions, and their corresponding outputs that encode rich semantic details. However, capturing and leveraging this information for tasks such as session similarity measurement, anomaly detection, and command category classification, can present a significant challenge especially when an attacker exploits noisy or obfuscated sessions.