Abstract
Large parts of scientific work relies on seeking for information in very large datasets and respective metadata (e.g., document repositories on the web, databases, local image collections). Based on a search string or even sample data as a query, information retrieval systems (IR systems) return lists of ranked items that match the query, together with a short preview of the item. Using search strings or example data, it is not easy to express certain information needs, however. In this extended abstract we discuss in what way the interaction of a user with an information retrieval (IR) system can optimized with human-aware collaborative planning strategies.
Originalsprache | Englisch |
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Titel | Humanities-Centred Artificial Intelligence, CHAI 2021 : CEUR Workshop Proceedings |
Erscheinungsdatum | 2021 |
Seiten | 31-39 |
Publikationsstatus | Veröffentlicht - 2021 |
Strategische Forschungsbereiche und Zentren
- Zentren: Zentrum für Künstliche Intelligenz Lübeck (ZKIL)
- Querschnittsbereich: Intelligente Systeme