metaSelektivität
MetaSelektivität is a term used in information retrieval and knowledge management to describe the ability of a system or process to select information based on its relevance not just to a specific query, but also to the broader context or purpose of the user's information need. It goes beyond simple keyword matching or topic relevance by considering higher-level factors such as the user's expertise, their current task, or the intended audience of the information.
Essentially, metaSelektivität involves a deeper understanding of what constitutes "useful" or "relevant" information in a given
Implementing metaSelektivität often requires sophisticated algorithms that can model user behavior, understand semantic relationships between concepts,