Predictive Process Approach for Email Response Recommendations

Process prediction requires analyzing traces to forecast future activities in a process. Traces can be found in information systems’ logs, such as email systems used by business actors. While email traces can aid in process prediction, their unstructured textual nature poses challenges for existing techniques. Additionally, predicting process-oriented emails goes beyond identifying future business process (BP) activities, as it also involves recommending the emails needed for BP actors to perform these activities. Current approaches to email prediction primarily focus on email management, with limited attention to BP contexts, and often only reach the BP discovery or email classification stages. This paper presents an overview of a novel process-activity aware email response recommendation system, designed to enhance both relevance and efficiency in business communications by offering BP knowledge and tailored response templates for incoming emails. The system provides specific recommendations on activities to include in responses, their intent (speech act), and associated business data. Unlike existing approaches, this work uniquely leverages unstructured email data to predict process activities for email responses and incorporates BP knowledge to offer BP-oriented guidance.