Valery Solovyev

CL
h-index15
5papers
121citations
Novelty18%
AI Score17

5 Papers

0.3CLJun 13, 2022
Automatic generation of a large dictionary with concreteness/abstractness ratings based on a small human dictionary

Vladimir Ivanov, Valery Solovyev

Concrete/abstract words are used in a growing number of psychological and neurophysiological research. For a few languages, large dictionaries have been created manually. This is a very time-consuming and costly process. To generate large high-quality dictionaries of concrete/abstract words automatically one needs extrapolating the expert assessments obtained on smaller samples. The research question that arises is how small such samples should be to do a good enough extrapolation. In this paper, we present a method for automatic ranking concreteness of words and propose an approach to significantly decrease amount of expert assessment. The method has been evaluated on a large test set for English. The quality of the constructed dictionaries is comparable to the expert ones. The correlation between predicted and expert ratings is higher comparing to the state-of-the-art methods.

0.7CLMay 29, 2017
Dynamics of core of language vocabulary

Valery D. Solovyev, Vladimir V. Bochkarev, Anna V. Shevlyakova

Studies of the overall structure of vocabulary and its dynamics became possible due to creation of diachronic text corpora, especially Google Books Ngram. This article discusses the question of core change rate and the degree to which the core words cover the texts. Different periods of the last three centuries and six main European languages presented in Google Books Ngram are compared. The main result is high stability of core change rate, which is analogous to stability of the Swadesh list.

2.0CLOct 4, 2014
Generating abbreviations using Google Books library

Valery D. Solovyev, Vladimir V. Bochkarev

The article describes the original method of creating a dictionary of abbreviations based on the Google Books Ngram Corpus. The dictionary of abbreviations is designed for Russian, yet as its methodology is universal it can be applied to any language. The dictionary can be used to define the function of the period during text segmentation in various applied systems of text processing. The article describes difficulties encountered in the process of its construction as well as the ways to overcome them. A model of evaluating a probability of first and second type errors (extraction accuracy and fullness) is constructed. Certain statistical data for the use of abbreviations are provided.

9.1AIAug 28, 2014
Mathematical Knowledge Representation: Semantic Models and Formalisms

Alexander Elizarov, Alexander Kirillovich, Evgeny Lipachev et al.

The paper provides a survey of semantic methods for solution of fundamental tasks in mathematical knowledge management. Ontological models and formalisms are discussed. We propose an ontology of mathematical knowledge, covering a wide range of fields of mathematics. We demonstrate applications of this representation in mathematical formula search, and learning.

3.5CLAug 30, 2012
Average word length dynamics as indicator of cultural changes in society

Vladimir V. Bochkarev, Anna V. Shevlyakova, Valery D. Solovyev

Dynamics of average length of words in Russian and English is analysed in the article. Words belonging to the diachronic text corpus Google Books Ngram and dated back to the last two centuries are studied. It was found out that average word length slightly increased in the 19th century, and then it was growing rapidly most of the 20th century and started decreasing over the period from the end of the 20th - to the beginning of the 21th century. Words which contributed mostly to increase or decrease of word average length were identified. At that, content words and functional words are analysed separately. Long content words contribute mostly to word average length of word. As it was shown, these words reflect the main tendencies of social development and thus, are used frequently. Change of frequency of personal pronouns also contributes significantly to change of average word length. The other parameters connected with average length of word were also analysed.