DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains
Ruben Agazzi, Renzo Alva Principe, Riccardo Pozzi, Marco Ripamonti, Matteo Palmonari
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.
BibTeX
@inproceedings{ijcai2025_daveaframeworkfo,
title = {DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains},
author = {Ruben Agazzi and Renzo Alva Principe and Riccardo Pozzi and Marco Ripamonti and Matteo Palmonari},
booktitle = {IJCAI 2025},
year = {2025}
}