2017 for the individual papers
by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
Data Analytics and Management in Data Intensive Domains
Selected Papers of the XIX International Conference on
Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2017)
Moscow, Russia, October 9-13, 2017.
* Institute of Informatics Problems,
Federal Research Center "Computer Science and Control"
of the Russian Academy of Sciences,
** Aristotle University, Department of Informatics,
*** Lomonosov Moscow State University,
DAMDID/RCDL conference is formed as a result of transformation of the
Russian Conference on Digital Libraries
with an intention to create a forum reflecting the urgent challenges of data organization, exploration
and analysis in various data intensive domains.
The transformation is planned so that the continuity with RCDL
should be preserved by the transformed conference as well as the RCDL community formed
during the sixteen years of its successful work will also be preserved.
DAMDID/RCDL allows authors to submit their paper either in English or in Russian.
For the papers in Russian the abstracts in English are provided and are placed on the first pages of the papers
right after abstracts in Russian.
Table of Contents
Keynote Talk 1
Keynote Talk 2
Data Analysis Projects in Astronomy
Semantic Web Techniques in DID
Special-purpose DID infrastructures 1
Special-purpose DID Infrastructures 2
System Efficiency Evaluation
Keynote Talk 3
Data Analysis Projects in Neuroscience
Specific Data Analysis Techniques
Ontological Models and Applications 1
Heterogeneous Database Integration
Text Analysis in Humanities 1
Data Analysis Projects in Various DID
Text analysis in humanities 2
Ontological Models and Applications 2
Organization of Experiments in Data Intensive Research
Digital Library Projects
Knowledge Representation and Discovery
Approaches for Problem Solving in DID
Application of Machine Learning
Machine Learning Methods Application to Search for Regularities in Chemical Data
Nadezhda N. Kiselyova,
Andrey V. Stolyarenko,
Victor A. Dudarev
Astrophysical Data Analytics based on Neural Gas Models, using the Classification of Globular Clusters as Playground
Thomas H. Puzi
Выявление аномалий в работе механизмов методами машинного обучения
(Anomaly Detection in Mechanisms Using Machine Learning)
Статистическая модель для распознавания смыслов в текстах иностранного языка с обучением на примерах из параллельных текстов
(Statistical Model for Recognition of Senses in Foreign Language Texts Trained by Examples from Parallel Texts)
2017-12-12: submitted by Leonid Kalinichenko, Sergey Stupnikov,
metadata incl. bibliographic data published under Creative Commons CC0
2017-12-12: published on CEUR-WS.org