DAVE is a framework for assisting the analysis of documents in knowledge-intensive domains, based on an entity-centric approach supported by annotations of named entities in the documents. DAVE supports search & filtering, document exploration, question answering, and knowledge refinement. It is released as an open-source project that the community can further develop. DAVE’s distinguishing features are: the integration of a chatbot interface based on recent RAG solutions into well-established entity-powered faceted search, the fusion of search and filtering features provided by entity-level annotations with the capability to ask questions on annotated documents; human-in-the-loop functions to consolidate knowledge while exploring information, allowing users to improve annotations from NLP algorithms.
Agazzi, R., Alva Principe, R., Pozzi, R., Ripamonti, M., Palmonari, M. (2025). DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence Montreal, Canada 16-22 August 2025 (pp.10984-10988) [10.24963/ijcai.2025/1246].
DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains
Alva Principe, Renzo;Pozzi, Riccardo
;Ripamonti, Marco;Palmonari, Matteo
2025
Abstract
DAVE is a framework for assisting the analysis of documents in knowledge-intensive domains, based on an entity-centric approach supported by annotations of named entities in the documents. DAVE supports search & filtering, document exploration, question answering, and knowledge refinement. It is released as an open-source project that the community can further develop. DAVE’s distinguishing features are: the integration of a chatbot interface based on recent RAG solutions into well-established entity-powered faceted search, the fusion of search and filtering features provided by entity-level annotations with the capability to ask questions on annotated documents; human-in-the-loop functions to consolidate knowledge while exploring information, allowing users to improve annotations from NLP algorithms.| File | Dimensione | Formato | |
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