Integrating information retrieval and data mining to discover project team coordination patterns

Abstract

This study integrates information retrieval and data mining techniques to discover project team coordination patterns from project documents written in Chinese. The coordination pattern of a project team describes the project execution process, including task category, execution sequence and duration, as well as the team member cooperation. The integration comprises two phases. The first phase extracts the most relevant keywords describing tasks executed by projects from unstructured or semi-structured documents using the mutual information estimate and the term weighting system. A concept hierarchy tree generated using the hierarchical clustering technique represents multiple levels of task categories. The second phase discovers project team coordination patterns through sequential pattern analysis. The proposed approach obtains encouraging results by mining coordination patterns from information system development projects. In the present era of the knowledge economy, the application of groupware to facilitate team coordination and collaboration streamlines the collection and analysis of project documents throughout the project life cycle. A project manager can visualize the project execution process of a team, and can anticipate the project outcomes based on discovered team coordination patterns. Accordingly, the proposed approach can be adapted to team projects that share certain characteristics with information system development projects.