Evidence-based healthcare integrates the best research evidence with clinical expertise in
order to make decisions based on the best practices available. In this context, the task of …

Information retrieval aims to retrieve the documents that answer users' queries. A typical
search process consists of different phases for which a variety of components have 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 …

Motivated by the recent success of end-to-end deep neural models for ranking tasks, we
present here a supervised end-to-end neural approach for query performance prediction …

The query performance prediction (QPP) task is to estimate the effectiveness of a search
performed in response to a query with no relevance judgments. Existing QPP methods do …

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 evaluate the …

The importance of query performance prediction has been widely acknowledged in the
literature, especially for query expansion, refinement, and interpolating different retrieval …

While large-scale pre-trained language models like BERT have advanced the state-of-the-
art in IR, its application in query performance prediction (QPP) is so far based on pointwise …

Modern Information Retrieval (IR) systems have become more and more complex, involving
a large number of parameters. For example, a system may choose from a set of possible …

To date, query performance prediction (QPP) in the context of content-based image retrieval
remains a largely unexplored task, especially in the query-by-example scenario, where the …