Abstract:

International and Russian-language data sources that provide information about Russian research-related organizations are considered. It is demonstrated that Russian-language data sources contain more information about Russian research-related organizations than most international data sources, but this information remains unavailable for English-language data sources. Experiments on comparison and integration of information about Russian research organizations in international and Russian data sources are outlined. Data sources such as GRID, Russian and English chapters of Wikipedia, Wikidata and eLIBRARY.ru are considered. The work is an intermediate step towards the creation of an open and extensible knowledge graph.

Abstract: Exponential size growth of such graphs as social networks, Internet graphs, etc. requires new approaches to their visualization. Along with node-link diagram representations, adjacency matrices and various hybrid representations are increasingly used for large graphs visualizations. This survey discusses new approaches to the visualization of large graphs using adjacency matrices and gives examples of applications where these approaches are used. We describe various types of patterns arising when adjacency matrices corresponding to modern networks are ordered, and algorithms making it possible to reveal these patterns. In particular, the use of matrix ordering methods in conjunction with algorithms looking for such graph patterns as stars, false stars, chains, near-cliques, full cliques, bipartite cores and near-bipartite cores enable users to create understandable visualizations of graphs with millions of vertices and edges. Examples of hybrid visualizations using node-link diagrams for representing sparse parts of a graph and adjacency matrices for representing dense parts are also given. The hybrid methods are used to visualize co-authorship networks, deep neural networks, to compare networks of the human brain connectivity, etc.

Abstract: The information visualization methods have been known as a tool providing the understanding of large data. The visualization of research publication collections is a special case of applying visualization methods to large data. This paper presents a survey of problems solved by means of visualization, document models and document analysis methods as well as of new approaches to visualization methods for research publication collections. Special attention is paid to the relation between the document analysis and visualization methods.

Abstract:

Cross-lingual entity alignment algorithms are designed to look for identical real-world objects in multilingual knowledge graphs. This problem occurs, for example, when searching for drugs manufactured in different countries under different names, or when searching for imported equipment. At the moment, there are several open-source libraries that collect implementations of entity alignment algorithms as well as test data sets for various languages. This paper describes experiments with several popular entity alignment algorithms applied to a Russian-English dataset. In addition to translating entity names from Russian to English, experiments on combining the various generators of entity name embeddings with the various generators of relational information embeddings have been conducted. In order to obtain more detailed information about the results of the EA approaches, an assessment by entity types, the number of relationships and attributes have been made. These experiments allowed us to significantly improve the accuracy of several EA algorithms on the English-Russian dataset.