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FADE – Intentional forgetting through cognitive-computational methods of prioritization, compression, and contraction of knowledge

What is your project about?

The continuous accumulation of information in an organization leads to a large amount of data, which often burden rather than facilitate work processes. The employee should be assisted to selectively hide information (eg via an old version) or to temporarily forget it (for example, from currently unimportant information). For this purpose, forgetting is analyzed both from a psychological and a computer-science perspective, and the existing knowledge structures in organizations are analyzed.

What are the objectives of the project?

The goal of FADE is to develop a formal framework that combines the models of forgetting developed in psychology with the methods of computer science (e.g., knowledge contraction). An interdisciplinary model of forgetting is realized, which is implemented in a software prototype and evaluated in the context of the cooperation partner IT & Media Center (ITMC) of the TU Dortmund.

How can organizations use the results?

By integrating the cognitive information system FADE into existing knowledge systems, the subjectively perceived flood of information can be reduced, for example in a help desk. For this purpose, a predictive selection of knowledge elements is carried out, which supports new and existing employees in your work processes. The prioritization and forgetting functions take into account whether information is situationally important, e.g. due to recurring events, or obsolete.

Project team

Prof. Dr. Beierle, Christoph Faculty of Mathematics and Computer Science Applicant
Sauerwald, Kai, M. Sc. Faculty of Mathematics and Computer Science

Prof. Dr. Kern-Isberner, Gabriele Faculty of Computer Science Applicant

apl. Prof. Dr. Dr. Ragni, Marco Cognitive Computation Lab Applicant
Dames, Hannah, M.Sc. Cognitive Computation Lab