DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains

Agazzi, Ruben; Alva Principe, Renzo; Pozzi, Riccardo; Ripamonti, Marco; Palmonari, Matteo

doi:10.24963/ijcai.2025/1246

DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains

Ruben Agazzi, Renzo Alva Principe, Riccardo Pozzi, Marco Ripamonti, Matteo Palmonari

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Demo Track. Pages 10984-10988.

https://doi.org/10.24963/ijcai.2025/1246

Keywords

Search: S: Applications
Natural Language Processing: NLP: Named entities
Natural Language Processing: NLP: Question answering
Humans and AI: HAI: Human-AI collaboration

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.

Ruben Agazzi, Renzo Alva Principe, Riccardo Pozzi, Marco Ripamonti, and Matteo Palmonari. 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, IJCAI-25. IJCAI, 10984–10988. https://doi.org/10.24963/ijcai.2025/1246

@inproceedings{ijcai2025p1246,
  title     = {DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains},
  author    = {Agazzi, Ruben and Alva Principe, Renzo and Pozzi, Riccardo and Ripamonti, Marco and Palmonari, Matteo},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {10984--10988},
  year      = {2025},
  month     = {8},
  note      = {Demo Track},
  doi       = {10.24963/ijcai.2025/1246},
  url       = {https://doi.org/10.24963/ijcai.2025/1246},
}

TY  - CPAPER
TI  - DAVE: A Framework for Assisted Analysis of Document Collections in Knowledge-Intensive Domains
AU  - Agazzi, Ruben
AU  - Alva Principe, Renzo
AU  - Pozzi, Riccardo
AU  - Ripamonti, Marco
AU  - Palmonari, Matteo
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 10984
EP  - 10988
DO  - 10.24963/ijcai.2025/1246
UR  - https://doi.org/10.24963/ijcai.2025/1246
ER  -