Conference paper
Conference paper
An enhanced approach to query performance prediction using reference lists
Abstract
We address the problem of query performance prediction (QPP) using reference lists. To date, no previous QPP method has been fully successful in generating and utilizing several pseudo-effective and pseudo-ineffective reference lists. In this work, we try to fill the gaps. We first propose a novel unsupervised approach for generating and selecting both types of reference lists using query perturbation and statistical inference. We then propose an enhanced QPP approach that utilizes both types of selected reference lists.
Related
Conference paper
Web Table Retrieval using Multimodal Deep Learning
Conference paper