Thesis supervisor: Ádám Csapó
Location of studies (in Hungarian): Corvinus Abbreviation of location of studies: CUB
Description of the research topic:
Effective knowledge management in both personal and business environments faces several key challenges, including seamless data capture, suitable organization, and effective recall. Seamless capture means that data acquisition should be a natural process across multiple modalities of data sources, requiring minimal time and cognitive effort from users. Suitable organization involves storing and tagging data, using automated or semi-automated methods, to support the widest possible range of downstream tasks. Effective recall ensures that the system provides contextually relevant search results tailored to the specific users and application scenarios. This research aims to explore how AI can address these challenges and enhance data acquisition, organization, and retrieval processes. The goal of this research is to develop novel solutions, including best practices, actionable guidelines, and AI-driven tools, to support effective knowledge management.
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