A Quantum-like Approach to Semantic Text Classification
In this work, we conduct a sentiment analysis of English-language reviews using a quantum-like (wave-based) model of text representation. This model is explored as an alternative to machine learning (ML) techniques for text classification and analysis tasks. Special attention is given to the problem...
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MDPI AG
2025-07-01
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| Online Access: | https://www.mdpi.com/1099-4300/27/7/767 |
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| author | Anastasia S. Gruzdeva Rodion N. Iurev Igor A. Bessmertny Andrei Y. Khrennikov Alexander P. Alodjants |
| author_facet | Anastasia S. Gruzdeva Rodion N. Iurev Igor A. Bessmertny Andrei Y. Khrennikov Alexander P. Alodjants |
| author_sort | Anastasia S. Gruzdeva |
| collection | DOAJ |
| description | In this work, we conduct a sentiment analysis of English-language reviews using a quantum-like (wave-based) model of text representation. This model is explored as an alternative to machine learning (ML) techniques for text classification and analysis tasks. Special attention is given to the problem of segmenting text into semantic units, and we illustrate how the choice of segmentation algorithm is influenced by the structure of the language. We investigate the impact of quantum-like semantic interference on classification accuracy and compare the results with those obtained using classical probabilistic methods. Our findings show that accounting for interference effects improves accuracy by approximately <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>15</mn><mo>%</mo></mrow></semantics></math></inline-formula>. We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. The results demonstrate that the quantum-like model can serve as a viable alternative or complement to traditional ML approaches. The model achieves classification precision and recall scores of around 0.8. Furthermore, the classification algorithm is readily amenable to optimization: the proposed procedure reduces the estimated computational complexity from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><msup><mi>n</mi><mn>2</mn></msup><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo>)</mo></mrow></semantics></math></inline-formula>. |
| format | Article |
| id | doaj-art-0eb3347e3de34f3589618173f6139b6f |
| institution | DOAJ |
| issn | 1099-4300 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-0eb3347e3de34f3589618173f6139b6f2025-08-20T03:07:54ZengMDPI AGEntropy1099-43002025-07-0127776710.3390/e27070767A Quantum-like Approach to Semantic Text ClassificationAnastasia S. Gruzdeva0Rodion N. Iurev1Igor A. Bessmertny2Andrei Y. Khrennikov3Alexander P. Alodjants4National Center for Cognitive Research, National Research University for Information Technology, Mechanics and Optics (ITMO), St. Petersburg 197101, RussiaFaculty of Software Engineering and Computer Systems, National Research University for Information Technology, Mechanics and Optics (ITMO), St. Petersburg 197101, RussiaFaculty of Software Engineering and Computer Systems, National Research University for Information Technology, Mechanics and Optics (ITMO), St. Petersburg 197101, RussiaInternational Center for Mathematical Modeling in Physics, Engineering, Economics and Cognitive Science, Linnaeus University, S-35195 Vaxjo-Kalmar, SwedenNational Center for Cognitive Research, National Research University for Information Technology, Mechanics and Optics (ITMO), St. Petersburg 197101, RussiaIn this work, we conduct a sentiment analysis of English-language reviews using a quantum-like (wave-based) model of text representation. This model is explored as an alternative to machine learning (ML) techniques for text classification and analysis tasks. Special attention is given to the problem of segmenting text into semantic units, and we illustrate how the choice of segmentation algorithm is influenced by the structure of the language. We investigate the impact of quantum-like semantic interference on classification accuracy and compare the results with those obtained using classical probabilistic methods. Our findings show that accounting for interference effects improves accuracy by approximately <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>15</mn><mo>%</mo></mrow></semantics></math></inline-formula>. We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. The results demonstrate that the quantum-like model can serve as a viable alternative or complement to traditional ML approaches. The model achieves classification precision and recall scores of around 0.8. Furthermore, the classification algorithm is readily amenable to optimization: the proposed procedure reduces the estimated computational complexity from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><msup><mi>n</mi><mn>2</mn></msup><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo>)</mo></mrow></semantics></math></inline-formula>.https://www.mdpi.com/1099-4300/27/7/767quantum-like heuristic algorithmstext classificationsentiment analysisinterferencevector-space language model |
| spellingShingle | Anastasia S. Gruzdeva Rodion N. Iurev Igor A. Bessmertny Andrei Y. Khrennikov Alexander P. Alodjants A Quantum-like Approach to Semantic Text Classification Entropy quantum-like heuristic algorithms text classification sentiment analysis interference vector-space language model |
| title | A Quantum-like Approach to Semantic Text Classification |
| title_full | A Quantum-like Approach to Semantic Text Classification |
| title_fullStr | A Quantum-like Approach to Semantic Text Classification |
| title_full_unstemmed | A Quantum-like Approach to Semantic Text Classification |
| title_short | A Quantum-like Approach to Semantic Text Classification |
| title_sort | quantum like approach to semantic text classification |
| topic | quantum-like heuristic algorithms text classification sentiment analysis interference vector-space language model |
| url | https://www.mdpi.com/1099-4300/27/7/767 |
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