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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.15759 |
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| _version_ | 1866910756204707840 |
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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 |