Turnaev A.., Apanovich Z..pdf287.45 KB

This paper describes a pipeline for extracting the author’s terms and definitions from mathematical texts. We used two models: one, for detecting mathematical formulas to clear text from noise and the other, for converting images into LaTeX formulas to restore the deleted formulas. Experimental data show that noise clearing is...

Article _1_Bul_45_.pdf1023.8 KB

This paper describes the experiments for the task on information extraction from news texts in Russian in a setting with a wide variety of types of entities and relations. We have adapted the SpERT model which uses the BERT network as a core for the joint extraction of entities and...

LV_Bull 2017_41_v2.pdf1.79 MB
This paper develops general concepts useful for extracting knowledge embedded in large graphs or datasets that have pair-wise relationships, such as relations of cause-effect type. Almost no underlying assumptions are made, other than that the data can be presented in terms of pair-wise relationships between objects/events. This assumption is used...
batura_et_al_bulletin_2015.pdf259.63 KB

The paper describes the generalization of the summarization algorithm of Niraj Kumar. The method proposed in the article uses the Link Grammar Parser. Our investigations are oriented to processing news articles, reviews from social networks, etc. We consider the possibility of applying this algorithm to estimate the relevance of posts...

batura_v8.pdf109.28 KB

The paper describes the methods of comparison of the sentences in a natural language for estimation of their similarity. To solve this problem, it is possible to use the semantic-syntactical relations between words constructed by the software system Link Grammar Parser. The results of our research are planned to be...