Studying the Variability of System Setting Effectiveness by Data Analytics and Visualization

International audienceSearch 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