Abstract
Quantum Computing (QC) is a research field that has been in the limelight in recent years. In fact, many researchers and practitioners believe that it can provide benefits in terms of efficiency and effectiveness when employed to solve certain computationally intensive tasks. In Information Retrieval (IR) and Recommender Systems (RS) we are required to process very large and heterogeneous datasets by means of complex operations, it is natural therefore to wonder whether QC could also be applied to boost their performance. The goal of this tutorial is to show how QC works to an audience that is not familiar with the technology, as well as how to apply the QC paradigm of Quantum Annealing (QA) to solve practical problems that are currently faced by IR and RS systems. During the tutorial, participants will be provided with the fundamentals required to understand QC and to apply it in practice by using a real D-Wave quantum annealer through APIs.
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Ferrari Dacrema, M., Pasin, A., Cremonesi, P., Ferro, N. (2024). Quantum Computing for Information Retrieval and Recommender Systems. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham. https://doi.org/10.1007/978-3-031-56069-9_47
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