Overview of QuantumCLEF 2024: The Quantum Computing Challenge for Information Retrieval and Recommender Systems at CLEF

Quantum Computing (QC) is an innovative research field that has gathered the interest of many researchers in the last few years. In fact, it is believed that QC could potentially revolutionize the way we solve very complex problems by dramatically decreasing the time required to solve them. Even though QC is still in its early stages of development, it is already possible to tackle some problems by means of quantum computers and to start catching a glimpse of its potential. Therefore, the aim of the QuantumCLEF lab is to raise awareness about QC and to develop and evaluate new QC algorithms to solve challenges that can be encountered when implementing Information Retrieval (IR) and Recommender Systems (RS) systems. Furthermore, this lab represents a good opportunity to engage with QC technologies which are typically not easily accessible. In this work, we present an overview of the first edition of QuantumCLEF, a lab that focuses on the application of Quantum Annealing (QA), a specific QC paradigm, to solve two tasks: Feature Selection for IR and RS systems, and Clustering for IR systems. There have been a total of 26 teams who registered for this lab and eventually 7 teams managed to successfully submit their runs following the lab guidelines. Due to the novelty of the topics, participants have been provided with many examples and comprehensive materials that allowed them to understand how QA works and how to program quantum annealers.