# quantum Case-Based Reasoning (qCBR)

arXiv: https://arxiv.org/abs/2104.00409 · HTML: https://mlsanity.com/paper/2104.00409/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 92 references that are in the map.
- First posted on arXiv 1 Apr 2021.

## Builds on (most cited first, 13 of 13)

- [Supervised learning with quantum enhanced feature spaces](https://mlsanity.com/paper/1804.11326/) (2018)
- [Quantum Machine Learning](https://mlsanity.com/paper/1611.09347/) (2016)
- [Efficient Learning for Deep Quantum Neural Networks](https://mlsanity.com/paper/1902.10445/) (2019)
- [A Tutorial on Principal Component Analysis](https://mlsanity.com/paper/1404.1100/) (2014)
- [word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method](https://mlsanity.com/paper/1402.3722/) (2014)
- [word2vec Parameter Learning Explained](https://mlsanity.com/paper/1411.2738/) (2014)
- [An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation](https://mlsanity.com/paper/1607.05368/) (2016)
- [Quantum support vector machine for big data classification](https://mlsanity.com/paper/1307.0471/) (2013)
- [Support vector machines on the D-Wave quantum annealer](https://mlsanity.com/paper/1906.06283/) (2019)
- [Qibo: a framework for quantum simulation with hardware acceleration](https://mlsanity.com/paper/2009.01845/) (2020)
- [Quantum machine learning and quantum biomimetics: A perspective](https://mlsanity.com/paper/2004.12076/) (2020)
- [A Quantum Information Retrieval Approach to Memory](https://mlsanity.com/paper/1310.3001/) (2013)
- [Introductory review to quantum information retrieval](https://mlsanity.com/paper/2008.13541/) (2020)

## Built on by (most cited first, 4 of 4)

- [Quantum Enhanced Filter: QFilter](https://mlsanity.com/paper/2104.03418/) (2021)
- [Fourier series weight in quantum machine learning](https://mlsanity.com/paper/2302.00105/) (2023)
- [BRAIN L: A book recommender system](https://mlsanity.com/paper/2302.00653/) (2023)
- [Quantum Machine Learning hyperparameter search](https://mlsanity.com/paper/2302.10298/) (2023)

## Abstract (arXiv)

Case-Based Reasoning (CBR) is an artificial intelligence approach to problem-solving with a good record of success. This article proposes using Quantum Computing to improve some of the key processes of CBR, such that a Quantum Case-Based Reasoning (qCBR) paradigm can be defined. The focus is set on designing and implementing a qCBR based on the variational principle that improves its classical counterpart in terms of average accuracy, scalability and tolerance to overlapping. A comparative study of the proposed qCBR with a classic CBR is performed for the case of the Social Workers' Problem as a sample of a combinatorial optimization problem with overlapping. The algorithm's quantum feasibility is modelled with docplex and tested on IBMQ computers, and experimented on the Qibo framework.