Applying natural language models and causal models to project management systems

Abstract

This thesis concerns itself with two problems. First, it examines ways in which to use natural language features in time-varying data in predictive models, specifically applied to the problem of software project maintenance. We attempted to integrate this natural language data into our existing predictive models for project management applications. Second, we began work on creating an easy-to-use, extensible causal modeling framework, a Python package called CEModels. This package allows users to create causal inference models using input data. We tested this framework on project management data as well.