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A Retrospective Context Mining Approach For Bootstrapping Personal Knowledge Assistants

Desiree Heim; Christian Jilek; Heiko Maus; Andreas Dengel
In: Pascal Reuss; Viktor Eisenstadt; Jakob Schönborn; Jero Schäfer (Hrsg.). Lernen, Wissen, Daten, Analysen 2022. GI-Workshop-Tage "Lernen, Wissen, Daten, Analysen" (LWDA-2022), October 5-7, Hildesheim, Germany, 2/2023.


Smart assistants supporting knowledge workers in their daily work are in demand nowadays. To provide individually tailored support, the assistants first have to gain knowledge about the knowledge worker and their information space. In our setting, the assistant should support the user according to their current mental context. To build the required mental context base, other approaches observe the human's interaction with information items like files, emails, etc. and infer contexts from this activity data. However, those procedures suffer from a cold start problem as the context base on which the assistant relies on is built alongside the observation. The context-mining approach introduced in this paper addresses this issue by relying only on document information that is available at the start-up time.


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