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Studying the variability of system setting effectiveness by data analytics and visualization

Déjean, Sébastien; Mothe, Josiane; Ullah, Md Zia

Authors

Sébastien Déjean

Josiane Mothe



Abstract

Search engines differ from their modules and parameters; defining the optimal system setting is challenging the more because of the complexity of a retrieval stream. The main goal of this study is to determine which are the most important system components and parameters in system setting, thus which ones should be tuned as the first priority. We carry out an extensive analysis of 20, 000 different system settings applied to three TREC ad-hoc collections. Our analysis includes zooming in and out the data using various data analysis methods such as ANOVA, CART, and data visualization. We found that the query expansion model is the most significant component that changes the system effectiveness, consistently across collections. Zooming in the queries, we show that the most significant component changes to the retrieval model when considering easy queries only. The results of our study are directly re-usable for the system designers and for system tuning.

Presentation Conference Type Conference Paper (Published)
Conference Name Experimental IR Meets Multilinguality, Multimodality, and Interaction: 10th International Conference of the CLEF Association (CLEF 2019)
Start Date Sep 9, 2019
End Date Sep 12, 2019
Online Publication Date Aug 3, 2019
Publication Date 2019
Deposit Date Mar 13, 2023
Publisher Springer
Pages 62-74
Series Title Lecture Notes in Computer Science
Series Number 11696
Series ISSN 1611-3349
Book Title Experimental IR Meets Multilinguality, Multimodality, and Interaction: 10th International Conference of the CLEF Association, CLEF 2019, Lugano, Switzerland, September 9--12, 2019, Proceedings
ISBN 978-3-030-28576-0
DOI https://doi.org/10.1007/978-3-030-28577-7_3
Keywords Information retrieval, Data analytics, Retrieval system modules, Effectiveness