NICA at Quantum Computing CLEF Tasks 2024

We present the models implemented by the NICA group for the Quantum Computing (QuantumCLEF) Shared Task at CLEF 2024. Our participation focused on Task 1A: Feature Selection (Information Retrieval Task). We propose a feature selection algorithm based on a quadratic unconstrained binary optimization (QUBO) problem, which selects a specified number of features considering their importance and redundancy. This task was solved using a real quantum computer provided by D-Wave on the MQ2007 and ISTELLA datasets. Our approach utilized “Shannon Entropy” to target the mutual information between each feature and the target value. In QuantumCLEF Task 1A, the organizers suggested training a LambdaMART model on the selected features and evaluating performance using the nDCG@10 metric. Our team achieved nDCG@10 scores of 0.4506 and 0.6211 for the MQ2007 and ISTELLA datasets, respectively.