Can we predict QPP? An approach based on multivariate outliers

no code implementations • 7 Feb 2024 • Adrian-Gabriel Chifu, Sébastien Déjean, Moncef Garouani, Josiane Mothe, Diégo Ortiz, Md Zia Ullah

Query performance prediction (QPP) aims to forecast the effectiveness of a search engine across a range of queries and documents.

Outlier Detection

Forward and Backward Feature Selection for Query Performance Prediction

no code implementations • 4 Dec 2019 • Sébastien Déjean, Radu Tudor Ionescu, Josiane Mothe, Md Zia Ullah

We found that: (1) our model based on a limited number of selected features is as good as more complex models for QPP and better than non-selective models; (2) our model is more efficient than complex models during inference time since it requires fewer features; (3) the predictive model is readable and understandable; and (4) one of our new QPP features is consistently selected across different collections, proving its usefulness.

feature selection Model Selection +1

Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM

no code implementations • 2 Jul 2015 • Léa Laporte, Rémi Flamary, Stephane Canu, Sébastien Déjean, Josiane Mothe

Feature selection in learning to rank has recently emerged as a crucial issue.

feature selection Learning-To-Rank