IRApr 26

FUTURAL: A Metasearch Platform for Empowering Rural Areas with Smart Solutions

arXiv:2604.238178.3Has Code
Predicted impact top 94% in IR · last 90 daysOriginality Synthesis-oriented
AI Analysis

This work provides a foundational platform for rural digital solutions, but the current MVP is limited to a single data source and represents an incremental step.

The FUTURAL project developed a Metasearch platform MVP using LLMs for natural language queries, targeting rural smart solutions. Evaluations showed high effectiveness, enabling future expansion to more services and datasets.

The FUTURAL project aims to provide a comprehensive suite of digital Smart Solutions (SS) across five critical domains to address pressing social and environmental issues. Central to this initiative is a robust Metasearch platform, which will not only serve as the primary access point to FUTURAL's solutions but also facilitate the search and retrieval of SS developed by other initiatives. This paper elaborates on the MVP implementation for the MetaSearch platform. It focuses on a single, open-source data service and harnesses the generative capabilities of Large Language Models (LLMs) to create a user-friendly natural language interface. The design of the Minimum Viable Product (MVP), the tools used for adapting LLMs to our specific application, and our comprehensive set of evaluation techniques are thoroughly detailed. The results from our evaluations demonstrate that our approach is highly effective and can be efficiently implemented in future iterations of the MVP. This groundwork paves the way for extending the platform to include additional services and diverse data sets from the FUTURAL project, enhancing its capacity to address a broader array of queries and datasets.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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