Towards Designing Linguistic Assessments Aggregation as a Distributed Neuroalgorithm

Demidovskij, Alexander; Babkin, Eduard

doi:10.1109/scm50615.2020.9198767

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…Tensor Representations may also be utilized to address the second question that arises while developing neurosymbolic systems: the expression of symbolic reasoning at the subsymbolic level. It has been demonstrated that simple algorithms (such as arithmetic operations) can be represented as a series of compiled neural networks [64,65]. On the other hand, there are other approaches that allow us to express complex symbolic algorithms in the form of neural network architectures.…”

Section: Application Of the Neurosymbolic Paradigm To The Development Of Modern Dssmentioning

confidence: 99%

Integrated neurosymbolic decision support systems: problems and opportunities

Demidovskij¹,

Babkin²

2021

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The current problem of developing new kinds of decision support systems for different categories of management personnel is addressed in this study. A critical feature of such systems is their distributed and decentralized nature, which enables the construction of next-generation information systems in the form of Multi-Agent Systems, Internet of Things, or Fog Computing Architectures. Parallel models of the dynamics of artificial neural networks are produced under such realistic circumstances, demonstrating their potential for addressing a variety of issues. The purpose of this study is to conduct a critical analysis of the problem of integrating Artificial Neural Networks with decision support systems using a corpus of relevant scholarly literature. To tackle this question, the Design Science Research methodology was considered. According to this methodology, a literary search strategy was established, scientific literature was collected and analyzed, and key comparisons between different solutions were emphasized. The study resulted in the presentation of the most important findings, outstanding issues, and potential areas of fundamental and applied solutions. A consistent trend toward the development of decision support systems based on integrated neural-network methods has been observed, which is efficient and cost-effective since it enables the creation of distributed and trainable decision support systems.

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Section: Application Of the Neurosymbolic Paradigm To The Development Of Modern Dssmentioning

confidence: 99%

Integrated neurosymbolic decision support systems: problems and opportunities

Demidovskij¹,

Babkin²

2021

Bus. Inform.

View full text Add to dashboard Cite

show abstract

Section: Application Of the Neurosymbolic Paradigm To The Development Of Modern Dssmentioning

confidence: 99%

Untitled

2021

Bus. Inform.

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The mission of the journal is to develop business informatics as a new field within both information technologies and management. It provides dissemination of latest technical and methodological developments, promotes new competences and provides a framework for discussion in the field of application of modern IT solutions in business, management and economics.The journal publishes papers in the areas of, but not limited to: modeling of social and economic systems, digital transformation of business, innovation management, information systems and technologies in business, data analysis and business intelligence systems, mathematical methods and algorithms of business informatics, business processes modeling and analysis, decision support in management.The journal is included into the list of peer reviewed scientific editions established by the Supreme Certification Commission of the Russian Federation.The journal is included into Web of Science Emerging Sources Citation Index (WoS ESCI), Russian Science Citation Index on the Web of Science platform (RSCI), EBSCO.

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Designing a Neural Network Primitive for Conditional Structural Transformations

Demidovskij

Babkin

2020

Artificial Intelligence

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Towards Designing Linguistic Assessments Aggregation as a Distributed Neuroalgorithm

Cited by 4 publications

References 20 publications

Integrated neurosymbolic decision support systems: problems and opportunities

Integrated neurosymbolic decision support systems: problems and opportunities

Untitled

Designing a Neural Network Primitive for Conditional Structural Transformations

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