The relative ineffectiveness of information retrieval systems is largely caused by the
inaccuracy with which a query formed by a few keywords models the actual user information …

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 …

Query performance prediction (QPP) is a core task in information retrieval. The QPP task is
to predict the retrieval quality of a search system for a query without relevance judgments …

A large class of entity extraction tasks from text that is either semistructured or fully
unstructured may be addressed by regular expressions, because in many practical cases …

The goal of a next basket recommendation (NBR) system is to recommend items for the next
basket for a user, based on the sequence of their prior baskets. We examine whether the …

Predicting the performance of a search engine for a given query is a fundamental and
challenging task in information retrieval. Accurate performance predictors can be used in …

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 …

In this paper we present Large Language Model Assisted Retrieval Model Ranking
(LARMOR), an effective unsupervised approach that leverages LLMs for selecting which …

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 …