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Том 53, № 5 (2019)
- Год: 2019
- Статей: 6
- URL: https://journal-vniispk.ru/0005-1055/issue/view/8987
Intelligent Systems
Comparison of Data Representation Languages in the Structure–Activity Problem
Аннотация
225-233
Information Analysis
A Probabilistic Algorithm for Calculating Similarities
Аннотация
In this paper, we describe a new probabilistic algorithm for calculating hypotheses as the results of similarities between training examples for a machine learning problem based on a binary similarity operation. Unlike previously proposed probabilistic algorithms, the order of accounting for training examples is fixed for all hypotheses. This algorithm is useful for implementation using a GPGPU. The main result of this paper is the independence of the order of the appearance of training examples of the probabilities of each similarity in the sample.
234-236
Academies of Sciences in Western Europe: Analysis of Activities, Web Content, and Webometric Indicators
Аннотация
This paper looks into issues associated with the Internet presence of the Academies of Sciences in several Western European countries. We identify the legal statuses of these academies and describe their administrative, financial, and informational interactions with government bodies, corporations, national and international scientific organizations, and individual researchers. A detailed analysis is conducted of the information posted on the websites of these academies, their interface features, language choices, available services, search engines, key webometric indicators, and newsletter mailing tools. Conclusions are drawn about the role of the websites of the academies in ensuring the availability and dissemination of science and technical information, including journal papers; about the creation of national and international scientific information space; and about the usefulness of these websites for Russian researchers.
237-249
The Jsm Method of Automated Research Support and Its Application in Intelligent Systems for Medicine
On the Heuristics of JSM Research (Additions to Articles)
Аннотация
The logical means of detecting empirical regularities using the JSM method of automated research support are considered. Generators of hypotheses about the causes and hypotheses about predictions that are stored in sequences of expandable fact bases are determined. Many “histories of possible worlds” are considered, where “world” refers to an expandable fact base. This set is used to determine empirical regularities, that is, empirical laws, tendencies, and weak tendencies. Empirical regularities are used to determine empirical modalities of necessity (for empirical laws), possibilities (for empirical tendencies), and weak possibilities (for weak empirical tendencies). The Propositional calculi of the class ERA are proposed, that is, modal logics with two empirical modalities of necessity and possibility such that they imitate abductive inference through the axioms of abduction (◻(p → q) & Tq) → ◻p), (◇(p → q) & Tq) → ◇p), where ◻, ◇, T are operators of necessity, possibility, and truth (“it is true that…”). A series of definitions related to the characterization of data mining using heuristics of the JSM method of automated research support is given.
250-282
Intellectual Mining of Patient Data with Melanoma for Identification of Disease Markers and Critical Genes
Аннотация
Genotypic (DNA mutations) and phenotyping data on patients with melanoma are analyzed to identify markers of early disease diagnosis and critical involved genes. An optimal mining method was chosen from those that are traditionally used in the field. This method allows one to analyze a set of terms. Automatic and interactive approaches were performed, which both allow a considerable reduction in the computational requirements. New melanoma-associated genes and candidate relapse markers were identified. Data mining was performed with the JSM method of automated support of scientific research (JSM ASSR).
283-287
An Intelligent System for Diagnostics of Pancreatic Diseases
Аннотация
288-294