Detection of New Intentions from Users Using the CRF Method for Software Service Evolution in Context-Aware Environments

User´s new requirements on a system are critical factors for driving software service evolution. New requirements usually arise when users are not satisfied with the existing system as often reflected in users´ divergent behaviors that can be detected through comparison with the known behavior patterns. In this paper, we propose a methodology that applies Conditional Random Fields (CRF) as the mathematical foundation for inferring users´ desires based on a peculiar form of observations and further exploring their new intentions that often imply new requirements. The potential new intentions detected by the CRF model will be verified and analyzed to elicit users´ new requirements for the system. As a result, the system should evolve through modifications or acquiring new functionalities to satisfy the new requirements. An experiment on a research library system is conducted to demonstrate how the new intentions are detected using the CRF method and used to drive system evolution.