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Bibliographic Details
Main Authors: Peikos, Georgios, Kusa, Wojciech, Symeonidis, Symeon
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.15759
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author Peikos, Georgios
Kusa, Wojciech
Symeonidis, Symeon
author_facet Peikos, Georgios
Kusa, Wojciech
Symeonidis, Symeon
contents 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
format Preprint
id arxiv_https___arxiv_org_abs_2412_15759
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ASPIRE: Assistive System for Performance Evaluation in IR
Peikos, Georgios
Kusa, Wojciech
Symeonidis, Symeon
Information Retrieval
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
title ASPIRE: Assistive System for Performance Evaluation in IR
topic Information Retrieval
url https://arxiv.org/abs/2412.15759