DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains
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.
Cite
Text
Agazzi et al. "DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains." International Joint Conference on Artificial Intelligence, 2025. doi:10.24963/IJCAI.2025/1246Markdown
[Agazzi et al. "DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains." International Joint Conference on Artificial Intelligence, 2025.](https://mlanthology.org/ijcai/2025/agazzi2025ijcai-dave/) doi:10.24963/IJCAI.2025/1246BibTeX
@inproceedings{agazzi2025ijcai-dave,
title = {{DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains}},
author = {Agazzi, Ruben and Principe, Renzo Arturo Alva and Pozzi, Riccardo and Ripamonti, Marco and Palmonari, Matteo},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2025},
pages = {10984-10988},
doi = {10.24963/IJCAI.2025/1246},
url = {https://mlanthology.org/ijcai/2025/agazzi2025ijcai-dave/}
}