Abstract: Since its inception, one of the biggest challenges for machine translation is meaning in context. Nowadays, the fields of artificial intelligence (AI) and human-computer interaction (HCI) are influencing each other like never before. Recent breakthroughs in the translation are made possible by a healthy AI-HCI collaboration. This article proposed a hierarchical structure of context for interactive machine translation environment tools, including local context, global context and contextual effects, based on translators' cognitive efforts when interacting with machines. This framework helps software developers, project managers and linguists who work with the interactive machine translation system better incorporate the contextual factors when collecting, managing and analyzing data from human feedback, which leads to relevant strategic plans for automatic segmentation as well as effective estimation for the degree of human involvement.