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Найдено документов в текущей БД: 2

Method of wellbeing estimation in territory management

/ T. Penkova // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2014. - Vol. 8582 LNCS, Is. PART 4. - P. 57-68, DOI 10.1007/978-3-319-09147-1_5 . -

Кл.слова (ненормированные):
Decision making support -- Territory management -- Wellbeing estimation -- Fuzzy logic -- Semantics -- Decision making support -- Index values -- Semantic interpretation -- Territory managements -- Wellbeing -- Decision making

Аннотация: This paper presents the new technique of territory wellbeing estimation based on creation of a geographically-oriented wellbeing standard and estimation of the territory wellbeing level. The author proposes a method of wellbeing level estimation that provides the calculation of territory wellbeing index taking into account various aspects of vital activity and semantic interpretation of index values using fuzzy logic. The practical result of the work is an implementation of suggested solutions for social monitoring of the territory. © 2014 Springer International Publishing.

Scopus

Держатели документа:
Institute of Computational Modelling SB RAS, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Penkova, T.; Пенькова, Татьяна Геннадьевна

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Matching disparate dimensions for analytical integration of heterogeneous data sources

/ A. Korobko, A. Korobko // 11th International Conference on Management of Digital EcoSystems, MEDES 2019 : Association for Computing Machinery, Inc, 2019. - 11th International Conference on Management of Digital EcoSystems, MEDES 2019 (12 November 2019 through 14 November 2019, ) Conference code: 156715. - P66-72, DOI 10.1145/3297662.3365809 . -

Кл.слова (ненормированные):
Analytical Data Integration -- FCA -- Heterogeneous Data -- OLAP -- Semantic Analysis -- Analytical models -- Ecosystems -- Mapping -- Semantics -- Virtual reality -- Analytical integration -- Conceptual analysis -- Heterogeneous data -- Heterogeneous data sources -- Multiple heterogeneous data source -- OLAP -- Semantic analysis -- Virtual integration -- Data integration

Аннотация: The paper presents the first steps towards an authorial integration methodology for heterogeneous data. Exposing information from multiple heterogeneous data sources demands a global (mediated) schema. We need a model to couple with the mismatches between schemata of different sources and to provide uniform access to the data. The virtual global schema is apparently more convenient for assembling big data sources because of useless time consumption during the processes of materialization and synchronization. Thus, an integral analytical model has been proposed as the global schema of heterogeneous data sources. The suggested model provides virtual integration of complex and diverse information for further analytical processing. It combines the original multidimensional design and lattice structure according to the formal conceptual analysis. The main goal of the paper is to suggest an approach to automatic mapping between the schemata of the disparate data sources and virtual integral analytical model with human moderation. © 2019 Copyright is held by the owner/author(s).

Scopus

Держатели документа:
Department of Applied Computer Science, ICM SB RAS, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Korobko, A.

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