Abstract: Over the last few years, Quantum Computing (QC) has captured the attention of numerous researchers from different fields since QC resources have become more applicable in solving practical problems. In the current landscape, Information Retrieval (IR) and Recommender Systems (RS) need to perform computationally intensive operations on massive and heterogeneous datasets. Therefore, it could be possible to use QC technologies such as Quantum Annealing (QA) to boost systems’ performance. The objective of this work is to present the second edition of the QuantumCLEF lab, which is composed of three tasks that aim at discovering and evaluating 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.
External IDs:dblp:conf/ecir/PasinDCCGF25
Loading