applying the bell’s test to chinese texts

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ID: 146796
2020
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Abstract
Search engines are able to find documents containing patterns from a query. This approach can be used for alphabetic languages such as English. However, Chinese is highly dependent on context. The significant problem of Chinese text processing is the missing blanks between words, so it is necessary to segment the text to words before any other action. Algorithms for Chinese text segmentation should consider context; that is, the word segmentation process depends on other ideograms. As the existing segmentation algorithms are imperfect, we have considered an approach to build the context from all possible n-grams surrounding the query words. This paper proposes a quantum-inspired approach to rank Chinese text documents by their relevancy to the query. Particularly, this approach uses Bell’s test, which measures the quantum entanglement of two words within the context. The contexts of words are built using the hyperspace analogue to language (HAL) algorithm. Experiments fulfilled in three domains demonstrated that the proposed approach provides acceptable results.
Reference Key
bessmertny2020entropyapplying Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Igor A. Bessmertny;Xiaoxi Huang;Aleksei V. Platonov;Chuqiao Yu;Julia A. Koroleva
Journal European journal of medicinal chemistry
Year 2020
DOI
10.3390/e22030275
URL
https://www.mdpi.com/1099-4300/22/3/275
Keywords
text mining

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