The design structure matrix (DSM) method is a powerful network modelling tool to highlight the system architecture via presenting the interactions between the elements comprising a system. In DSM, measuring the interaction strength between elements is the first and crucial step. However, since the system elements are generally pre-identified by experts, their interaction relationships are often obtained from experts’ evaluation, which is time consuming and error-prone. To address this critical issue, in this paper, we aim to discover the hidden tasks of a process and their interactions from email logs with domain-specific contents. To this purpose, we have proposed a three-stage numerical DSM modeling approach, where text mining and clustering techniques are studied to discover hidden tasks. Furthermore, a metric concerning the measurement of interaction strength based on the overlapping time and the volume of exchanged information is presented. A case study is provided based on the emails collected from a design project.