Non-separability Effects in Cognitive Semantic Retrieving

Platonov, A.V.; Bessmertny, Igor; Semenenko, Evgeny K.; Alodjants, A. P.

doi:10.1007/978-3-030-25913-6_2

Cited by 4 publications

(5 citation statements)

References 9 publications

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“…The wide polysemy of Chinese words makes searching documents by patterns inefficient. From this point of view, it is interesting to apply to Chinese texts an approach that was validated for English in [ 10 ]. This approach is based on vector word representation and it incorporates the context of words into the search process.…”

Section: Methodsmentioning

confidence: 99%

“…This approach is based on vector word representation and it incorporates the context of words into the search process. The authors of [ 10 ] used quantum mathematical formalism and Bell’s test as a measure of documents’ relevance to the query. Unlike in [ 10 ], in this work, an asymmetric HAL built on the n-gram segmentation principle was used.…”

Section: Methodsmentioning

confidence: 99%

“…Document relevance to the query could be measured as a document vector’s projection to the query plane built by two query words. In [ 9 , 10 ], Bell’s test was used to assess the entanglement of words from a query in English texts as a measure of document relevance.…”

Section: Introductionmentioning

confidence: 99%

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Applying the Bell’s Test to Chinese Texts

Bessmertny

Huang

Platonov

et al. 2020

Entropy

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Applying the Bell’s Test to Chinese Texts

Bessmertny

Huang

Platonov

et al. 2020

Entropy

Self Cite

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“…In particular, quantum probabilistic approaches may be useful for resolving and the explanation of judgments and decisions associated with so-called “cognitive biases”, which appear as a result of a violation of the sure-thing principle [ 80 ]. The “interaction” of humans with the classical environment represents a new, quantum-like paradigm in modern social and cognitive sciences [ 81 ]. The classical environment, which may be represented by some AIAs, recommendation systems, information retrieval systems, etc., specifies some quantum-like (contextual) paradigm that may also be resolved in the framework of quantum instruments approach [ 82 ].…”

Section: State Of the Artmentioning

confidence: 99%

Emerging Complexity in Distributed Intelligent Systems

Guleva

Shikov

Bochenina

et al. 2020

Entropy

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Distributed intelligent systems (DIS) appear where natural intelligence agents (humans) and artificial intelligence agents (algorithms) interact, exchanging data and decisions and learning how to evolve toward a better quality of solutions. The networked dynamics of distributed natural and artificial intelligence agents leads to emerging complexity different from the ones observed before. In this study, we review and systematize different approaches in the distributed intelligence field, including the quantum domain. A definition and mathematical model of DIS (as a new class of systems) and its components, including a general model of DIS dynamics, are introduced. In particular, the suggested new model of DIS contains both natural (humans) and artificial (computer programs, chatbots, etc.) intelligence agents, which take into account their interactions and communications. We present the case study of domain-oriented DIS based on different agents’ classes and show that DIS dynamics shows complexity effects observed in other well-studied complex systems. We examine our model by means of the platform of personal self-adaptive educational assistants (avatars), especially designed in our University. Avatars interact with each other and with their owners. Our experiment allows finding an answer to the vital question: How quickly will DIS adapt to owners’ preferences so that they are satisfied? We introduce and examine in detail learning time as a function of network topology. We have shown that DIS has an intrinsic source of complexity that needs to be addressed while developing predictable and trustworthy systems of natural and artificial intelligence agents. Remarkably, our research and findings promoted the improvement of the educational process at our university in the presence of COVID-19 pandemic conditions.

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“…During the recent years the mathematical formalism of quantum theory started to be actively applied to a variety of problems outside of physics (see, e.g., [1]). In particular, applications to information retrieval are very promising, see, e.g., book [2] for the collection of recent papers and articles [3]- [5]. The aim of this brief introductory review is to stimulate non-experts in information retrieval to start working in this area of research, especially those from quantum information theory and those working with quantum-like models in decision making.…”

Section: Introductionmentioning

confidence: 99%

Introductory review to quantum information retrieval

Lebedev¹,

Khrennikov²

2020

Preprint

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Recently people started to understand that applications of the mathematical formalism of quantum theory are not reduced to physics. Nowadays, this formalism is widely used outside of quantum physics, in particular, in cognition, psychology, decision making, information processing, especially information retrieval. The latter is very promising. The aim of this brief introductory review is to stimulate research in this exciting area of information science. This paper is not aimed to present a complete review on the state of art in quantum information retrieval.

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Non-separability Effects in Cognitive Semantic Retrieving

Cited by 4 publications

References 9 publications

Applying the Bell’s Test to Chinese Texts

Applying the Bell’s Test to Chinese Texts

Emerging Complexity in Distributed Intelligent Systems

Introductory review to quantum information retrieval

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