ASPIRE: Assistive System for Performance Evaluation in IR
Abstract
Information Retrieval (IR) evaluation involves far more complexity than merely presenting performance measures in a table. Researchers often need to compare multiple models across various dimensions, such as the Precision-Recall trade-off and response time, to understand the reasons behind the varying performance of specific queries for different models. We introduce ASPIRE (Assistive System for Performance Evaluation in IR), a visual analytics tool designed to address these complexities by providing an extensive and user-friendly interface for in-depth analysis of IR experiments. ASPIRE supports four key aspects of IR experiment evaluation and analysis: single/multi-experiment comparisons, query-level analysis, query characteristics-performance interplay, and collection-based retrieval analysis. We showcase the functionality of ASPIRE using the TREC Clinical Trials collection. ASPIRE is an open-source toolkit available online: https://github.com/GiorgosPeikos/ASPIRE
Cite
@article{arxiv.2412.15759,
title = {ASPIRE: Assistive System for Performance Evaluation in IR},
author = {Georgios Peikos and Wojciech Kusa and Symeon Symeonidis},
journal= {arXiv preprint arXiv:2412.15759},
year = {2024}
}
Comments
Accepted as a demo paper at the 47th European Conference on Information Retrieval (ECIR)