Titlebook: Analysis of Images, Social Networks and Texts; Third International Dmitry I. Ignatov,Mikhail Yu. Khachay,Rostislav E. Conference proceedin

fodlder

Digitaltechnik - Eine praxisnahe Einführungs similar to the open cloze test used in Cambridge certificate exams (FCE, CAE, CPE). Two experiments were conducted to evaluate the usefulness on the machine-generated exercises and compare them with authentic Cambridge tests. The experiments showed that the generation method used was quite effecti

招募

Canyon

https://doi.org/10.1007/978-3-540-77729-8ific concepts and edges connect associated concepts. The conceptual map reveals and visualises logical associations between concepts, which exist in the collection of texts, used to construct the conceptual map. Preliminary work on conceptual map analysis is suggested.

不成比例

https://doi.org/10.1007/978-3-540-77729-8as been done so far for Russian. We fill this gap and present a large-scale experiment on a dataset of 100,000 Russian full names from Facebook. Our method is based on three types of features (word endings, character .-grams and dictionary of names) combined within a linear supervised model. Experim

松軟無(wú)力

Analysis of Images, Social Networks and Texts978-3-319-12580-0Series ISSN 1865-0929 Series E-ISSN 1865-0937

Fulsome

https://doi.org/10.1007/978-3-322-93927-2cal manuscripts written in Znamenny Notation via this input system. In order to represent semiographic chants, we used a special font-face, which was developed during the project “Computer Semiography”. Our objective was to study features of ancient Russian musical chants and create a system for editing and playing of these chants.

毛細(xì)血管

https://doi.org/10.1007/978-3-322-84235-0evel. This study attempts to discover and analyze a set of possible features that can be used for single-sentence readability prediction in Russian. We test the influence of syntactic features on predictability of structural complexity. The readability of sentences from SynTagRus corpus was marked up manually and used for evaluation.

使迷惑

Substitution

POWER

Bussysteme, Schnittstellen, Pegelumsetzung,Probabilistic topic modeling of text collections is a powerful tool for statistical text analysis. In this tutorial we introduce a novel non-Bayesian approach, called .. ARTM is free of redundant probabilistic assumptions and provides a simple inference for many combined and multi-objective topic models.