[1] NADKARNI P M, OHNO MACHADO L, CHAPMAN W W. Natural language processing: An introduction[J]. Journal of the American Medical Informatics Association, 2011, 18(5): 544-551.
[2] ABIODUN O I, JANTAN A, OMOLARA A E, et al. State-of-the-art in artificial neural network applications: A survey[J]. Heliyon, 2018, 4(11): e00938.
[3] CLARK S, COECKE B, SADRZADEH M. A compositional distributional model of meaning[C]//Proceedings of the 2nd Quantum Interaction Symposium. 2008: 133-140.
[4] WANG B, ZHANG P, LI J, et al. Exploration of quantum interference in document relevance judgement discrepancy[J]. Entropy, 2016, 18(4): 144.
[5] SERGUEEV N, GUO H. NEGF-DFT: A first principles formalism for modeling molecular electronics[G]//High Performance Computing Systems and Applications, 2003: 2-4.
[6] KASIM M F, VINKO S M. Learning the exchange-correlation functional from nature with fully differentiable density functional theory[J]. arXiv preprint arXiv: 2102.04229, 2021.
[7] FEYNMAN R P. Simulating physics with computers[M]. Feynman and Computation. CRC Press, 2018: 133-153.
[8] VAN RIJSBERGEN C J. The geometry of information retrieval[M]. Cambridge University Press, 2004.
[9] WANG B, ZHANG P, LI J, et al. Exploration of quantum interference in document relevance judgement discrepancy[J]. Entropy, 2016, 18(4): 144.
[10] JIANG Y, ZHANG P, GAO H, et al. A quantum interference inspired neural matching model for ad-hoc retrieval[C]//Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020: 19-28.
[11] XIE M, HOU Y, ZHANG P, et al. Modeling quantum entanglements in quantum language models[C]//Proceedings of the 24th International Joint Conference on Artificial Intelligence,2015: 1362-1368.
[12] GLEASON A M. Measures on the closed subspaces of a Hilbert space[M]. The Logico-Algebraic Approach to Quantum Mechanics. Springer, Dordrecht, 1975: 123-133.
[13] WARMUTH M K, KUZMIN D. Bayesian generalized probability calculus for density matrices[J]. Machine Learning, 2010, 78(1): 63-101.
[14] SORDONI A, NIE J Y, BENGIO Y. Modeling term dependencies with quantum language models for IR[C]//Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2013: 653-662.
[15] ZHANG P, NIU J, SU Z, et al. End-to-end quantum-like language models with application to question answering[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2018, 32(1): 5666-5673.
[16] LI Q, WANG B, MELUCCI M. CNM: an interpretable complex-valued network for matching[J]. arXiv preprint arXiv: 1904.05298, 2019.
[17] GODDARD, C, WIERZBICKA, A. Semantic and lexical universals: Theory and empirical findings[M]. John Benjamins Publishing Company, 1994: 20.
[18] WANG B, ZHAO D, LIOMA C, et al. Encoding word order in complex embeddings[J]. arXiv preprint arXiv: 1912.12333, 2019.
[19] SADRZADEH M. High level quantum structures in linguistics and multi agent systems[G]//AAAI Spring Symposium: Quantum Interaction, 2007: 9-16.
[20] WIDDOWS D, WIDDOWS D. Geometry and meaning[M]. Stanford: CSLI Publications, 2004.
[21] COECKE B, SADRZADEH M, CLARK S. Mathematical foundations for a compositional distributional model of meaning[J]. arXiv preprint arXiv: 1003.4394, 2010.
[22] MITCHELL J, LAPATA M. Composition in distributional models of semantics[J]. Cognitive Science, 2010, 34(8): 1388-1429.
[23] PRELLER A. Towards discourse representation via pregroup grammars[J]. Journal of Logic Language Information, 2007,16(2): 173-194.
[24] BASILE I, TAMBURINI F. Towards quantum language models[C]//Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2017: 1840-1849.
[25] ZHANG P, SU Z, ZHANG L, et al. A quantum many-body wave function inspired language modeling approach[C]//Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018: 1303-1312.
[26] COECKE B, DE FELICE G, MEICHANETZIDIS K, et al. Foundations for near-term quantum natural language processing[J]. arXiv preprint arXiv: 2012.03755, 2020.
[27] ZENG W, COECKE B. Quantum algorithms for compositional natural language processing[J]. arXiv preprint arXiv: 1608.01406, 2016.
[28] R^EHC^EK J, HRADIL Z, JEEK M. Iterative algorithm for reconstruction of entangled states[J]. Physical Review A, 2001, 63(4): 040303.
[29] LVOVSKY A I. Iterative maximum-likelihood reconstruction in quantum homodyne tomography[J]. Journal of Optics b: Quantum and Semiclassical Optics, 2004, 6(6): S556.
[30] WIEBE N, KAPOOR A, SVORE K M. Quantum nearest-neighbor algorithms for machine learning[J]. Quantum Information and Computation, 2015, 15(3-4): 318-358.
[31] ZHANG L, ZHANG P, MA X, et al. A generalized language model in tensor space[J]//Proceedings of the AAAI Conference on Artificial Intelligence, 2019, 33(01): 7450-7458.
[32] ZHANG P, ZHANG J, MA X, et al. 2021 Text[EB/OL].https://openveview.net Horum?id=ullTx2LOBMV.[2021-07-13]
[33] AERTS D, GABORA L. A theory of concepts and their combinations I[J]. Kybernetes, 2005,34(1/2): 151-175.
[34] AERTS D, GABORA L. A theory of concepts and their combinations II[J]. To appear in Kybernetes, 2005: 34(1/2): 192-221.
[35] COECKE B. Automated quantum reasoning: Non logic-semi-logic-hyper-logic[G]//AAAI Spring Symposium: Quantum Interaction, 2007: 31-38.
[36] LI Q, MELUCCI M, TIWARI P. Quantum language model-based query expansion[C]//Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval, 2018: 183-186.
[37] WANG B, ZHANG P, LI J, et al. Exploration of quantum interference in document relevance judgement discrepancy[J]. Entropy, 2016, 18(4): 144.
[38] LI Q, LI J, ZHANG P, et al. Modeling multi-query retrieval tasks using density matrix transformation[C]//Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015: 871-874.
[39] MEICHANETZIDIS K, TOUMI A, DE FELICE G, et al. Grammar-aware question-answering on quantum computers[J]. arXiv preprint arXiv: 2012.03756, 2020.
[40] ZHANG Y, SONG D, LI X, et al. Unsupervised sentiment analysis of twitter posts using density matrix representation[C]//Proceedings of European Conference on Information Retrieval. Springer, Cham, 2018: 316-329.
[41] ZHANG Y, LI Q, SONG D, ET AL. Quantum-inspired interactive networks for conversational sentiment analysis[C]//Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019: 5436-5442.
[42] ZHANG Y, SONG D, LI X, et al. A quantum-like multimodal network framework for modeling interaction dynamics in multiparty conversational sentiment analysis[J]. Information Fusion, 2020, 62: 14-31.
[43] NIELSEN M A, CHUANG I L. Quantum computation and quantum information[M]. Cambridge University Press, 2010: 80-97.
[44] CLARK S, PULMAN S. Combining symbolic and distributional models of meaning[C]//Proceedings of the 2007 AAAI Spring Symposium, 2007.
[45] OH S, CHOI J, KIM J. A tutorial on quantum convolutional neural networks[C]//Proceedings of the International Conference on Information and Communication Technology Convergence. IEEE, 2020: 236-239.
[46] CHEN S Y C, YOO S, FANG Y L L. Quantum long short-term memory[C]//Proceedings of ICASSP IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2022: 8622-8626.
[47] LI G, ZHAO X, WANG X. Quantum self-attention neural networks for text classification[J]. arXiv preprint arXiv: 2205.05625, 2022.
[48] LLOYD S, SCHULD M, IJAZ A, et al. Quantum embeddings for machine learning[J]. arXiv preprint arXiv: 2001.03622, 2020.
[49] Mindspore.[EB/OL].https://www.mindspore.cn/.[2020-09-26]