ML Anthology

KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces

Alexander Rogiers, Maarten Buyl, Bo Kang, Tijl De Bie
ECML-PKDD 2024 pp. 409-412
doi:10.1007/978-3-031-70371-3_30 /ecmlpkdd/2024/rogiers2024ecmlpkdd-kamerraad/

Abstract

KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information. The tool extracts and concisely summarizes key excerpts from parliamentary proceedings, followed by the potential for interaction based on generative AI that allows users to steadily build up their understanding. KamerRaad’s front-end, built with Streamlit, facilitates easy interaction, while the back-end employs open-source models for text embedding and generation to ensure accurate and relevant responses. By collecting feedback, we intend to enhance the relevancy of our source retrieval and the quality of our summarization, thereby enriching the user experience with a focus on source-driven dialogue.

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Cite

Text

Rogiers et al. "KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2024. doi:10.1007/978-3-031-70371-3_30

Markdown

[Rogiers et al. "KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2024.](https://mlanthology.org/ecmlpkdd/2024/rogiers2024ecmlpkdd-kamerraad/) doi:10.1007/978-3-031-70371-3_30

BibTeX

@inproceedings{rogiers2024ecmlpkdd-kamerraad,
  title     = {{KamerRaad: Enhancing Information Retrieval in Belgian National Politics Through Hierarchical Summarization and Conversational Interfaces}},
  author    = {Rogiers, Alexander and Buyl, Maarten and Kang, Bo and De Bie, Tijl},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2024},
  pages     = {409-412},
  doi       = {10.1007/978-3-031-70371-3_30},
  url       = {https://mlanthology.org/ecmlpkdd/2024/rogiers2024ecmlpkdd-kamerraad/}
}