Igor A. Bolshakov

444 citations
16 papers · 47 indexed · h-index 4
Topics
Natural Language Processing Techniques (7 papers)Spanish Linguistics and Language Studies (5 papers)Topic Modeling (4 papers)
Journals
Journal of Mathematical SciencesRevista signosProcesamiento del lenguaje natural
Partner nations
MexicoRussia

In The Last Decade

Igor A. Bolshakov

14 papers receiving 40 citations

Peers

Igor A. Bolshakov
Comparison fields: 5 of 18
  • Artificial Intelligence 39
  • Computer Vision and Pattern Recognition 16
  • Language and Linguistics 5
  • Information Systems 4
  • Computational Theory and Mathematics 3
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Citations per field
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Citations per year

Countries citing papers authored by Igor A. Bolshakov

Since Specialization
Citations

This map shows the geographic impact of Igor A. Bolshakov's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Igor A. Bolshakov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor A. Bolshakov more than expected).

Fields of papers citing papers by Igor A. Bolshakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Igor A. Bolshakov. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Igor A. Bolshakov. The network helps show where Igor A. Bolshakov may publish in the future.

Co-authorship network of co-authors of Igor A. Bolshakov

This figure shows the co-authorship network connecting the top 25 collaborators of Igor A. Bolshakov. A scholar is included among the top collaborators of Igor A. Bolshakov based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Igor A. Bolshakov. Igor A. Bolshakov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 1
2
Using Selectional Preferences for Extending a Synonymous Paraphrasing Method in Steganography
15
3 2
4
On detection of malapropisms by multistage collocation testing
9
5
Word combinations as an important part or modern electronic dictionaries
1
6
Análisis Sintáctico para el Español Basado en el Formalismo de la Teoría Significado-Texto.
0
7 5
8 1
9
Una aproximación para resolución de ambigüedad estructural empleando tres mecanismos diferentes
1
10
Avances y perspectivas de procesamiento automático de lenguaje natural. Cuento de una máquina parlante
1
11
Diccionario de patrones de manejo sintáctico para análisis de textos en español.
2
12 1
13 1
14 1
15 3
16
PROBLEMS OF THE STATISTICAL THEORY OF RADAR
3

About Igor A. Bolshakov

Igor A. Bolshakov is a scholar working on Language and Linguistics, Artificial Intelligence and Computational Theory and Mathematics, having authored 16 papers that have together received 47 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Spanish Linguistics and Language Studies (5 papers) and Topic Modeling (4 papers). The work is most often cited by research in Artificial Intelligence (39 citations), Computer Vision and Pattern Recognition (16 citations) and Language and Linguistics (5 citations). Igor A. Bolshakov has collaborated with scholars based in Mexico and Russia. Frequent co-authors include Alexander Gelbukh, Hiram Calvo, Grigori Sidorov and Alexandre Smirnov. Their work appears in journals such as Journal of Mathematical Sciences, Revista signos and Procesamiento del lenguaje natural.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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