Publication
Context-centric proactive information delivery for Knowledge Work support: Opportunities, challenges, and directions. An Annual Review of Information Science and Technology (ARIST)
Mahta Bakhshizadeh; Christian Jilek; Markus Schröder; Heiko Maus; Andreas Dengel
In: Journal of the Association for Information Science and Technology (JASIST), Pages 1-25, Wiley, 3/2026.
Abstract
Context-centric proactive information delivery (PID) is a relatively underexplored domain within recommender systems (RS) aimed at enhancing Knowledge
Workers' productivity by proactively providing relevant information during digital tasks. These RS anticipate user needs by leveraging personal knowledge modeling, context recognition, and recommendation techniques to deliver timely and relevant resources without requiring explicit searches. Developing such RS faces various challenges in addition to common challenges within the broader RS landscape. These challenges range from datarelated issues, such as handling heterogeneous and noisy data, to user-centric concerns, including privacy, explainability, and the lack of explicit feedback, as well as system and algorithmic challenges like cross-application context modeling and scalability. This paper explores the opportunities, challenges, and future directions for PID, outlining key advancements and enabling technologies that support its development.
Projects
- CoMem - Corporate Memory
- SensAI - Self-organizing Personal Knowledge Assistants in Evolving Corporate Memories