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Applying the Bell's Test to Chinese Texts.

Igor A Bessmertny1, Xiaoxi Huang1, Aleksei V Platonov2

  • 1School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China.

Entropy (Basel, Switzerland)
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This study introduces a novel quantum-inspired method for ranking Chinese text documents by relevance. It leverages word entanglement and context analysis to improve search accuracy for context-dependent languages.

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Area of Science:

  • Natural Language Processing
  • Information Retrieval
  • Quantum Computing Applications

Background:

  • Traditional search engines excel with alphabetic languages but struggle with context-dependent languages like Chinese.
  • Chinese text lacks word delimiters, necessitating accurate word segmentation for effective processing.
  • Existing Chinese text segmentation algorithms often fall short in capturing contextual nuances.

Purpose of the Study:

  • To propose a quantum-inspired approach for enhancing the relevancy ranking of Chinese text documents.
  • To address the challenges of context dependency and word segmentation in Chinese information retrieval.

Main Methods:

  • Developing a context-aware approach using n-grams surrounding query words.
  • Implementing a quantum-inspired ranking model utilizing Bell's test to measure word entanglement.
  • Employing the Hyperspace Analogue to Language (HAL) algorithm for building word contexts.

Main Results:

  • The proposed quantum-inspired approach demonstrated acceptable performance in ranking Chinese text documents.
  • The method effectively utilizes word entanglement and contextual information for improved relevancy assessment.
  • Experimental results across three domains validate the efficacy of the novel approach.

Conclusions:

  • Quantum-inspired methods offer a promising avenue for improving information retrieval in context-dependent languages.
  • Measuring word entanglement via Bell's test can enhance the understanding of semantic relationships in Chinese text.
  • The developed approach provides a viable solution for more accurate Chinese document ranking.