Abstract Evaluation in Information Retrieval (IR) relies on post-hoc empirical procedures,
which are time-consuming and expensive operations. To alleviate this, Query Performance …

Information retrieval (IR) has changed considerably in recent years with the expansion of the
World Wide Web and the advent of modern and inexpensive graphical user interfaces and …

In this work, we propose a novel framework to devise features that can be used by Query
Performance Prediction (QPP) models for Neural Information Retrieval (NIR). Using the …

Predicting query performance, that is, the effectiveness of a search performed in response to
a query, is a highly important and challenging problem. We present a novel approach to this …

Long queries frequently contain many extraneous terms that hinder retrieval of relevant
documents. We present techniques to reduce long queries to more effective shorter ones …

The focus of research on query performance prediction is to predict the effectiveness of a
query given a search system and a collection of documents. If the performance of queries …

Query performance prediction (QPP) is a core task in information retrieval (IR) that aims at
predicting the retrieval quality for a given query without relevance judgments. QPP has been …

Abstract Query Performance Prediction (QPP) has been studied extensively in the IR
community over the last two decades. A by-product of this research is a methodology to …

This article studies a novel problem in image search. Given a text query and the image
ranking list returned by an image search system, we propose an approach to automatically …

Query performance prediction (QPP) methods, which aim to predict the performance of a
query, often rely on evidences in the form of different characteristic patterns in the …