Abstract Summary
Quantum Computing (QC) is a research field that has been in the limelight in recent years. In fact, this new paradigm has the potential to revolutionize the way we currently solve problems by leveraging quantum-mechanical phenomena, which allow quantum computers to solve specific problems more efficiently than traditional computers. As quantum computers are starting to become more available, our objective is to investigate the application of QC within the Information Retrieval (IR) and Recommender Systems (RS) fields. In fact, IR and RS systems perform computationally intensive operations on extensive datasets, and using QC in their pipeline could be useful to improve their efficiency and, in some cases, effectiveness. Thus, in this work, we present the third edition of the QuantumCLEF lab, the first lab that allows participants to use real quantum computers for solving IR and RS tasks. The lab is composed of three main tasks that aim at discovering and evaluating Quantum Annealing (QA) approaches compared to their traditional counterpart while also establishing collaborations among researchers from different fields to harness their knowledge and skills to solve the considered challenges and promote the usage of QA. Moreover, if quantum resources are available, we plan to introduce a gate-based task for more-experienced researchers.
