Ján Žižka

1.9k citations
113 papers · 1.2k indexed · h-index 20

Ján Žižka

101 papers receiving 1.1k citations

Peers

Ján Žižka
Comparison fields: 5 of 145
  • Hepatology 135
  • Soil Science 135
  • Biomaterials 96
  • Immunology and Allergy 40
  • Environmental Chemistry 62
Replace Vı́ctor Ruiz with:
Vı́ctor Ruiz Mexico
Takuma Watanabe Japan
Rui Hou China
Qian Ye China
Liang Zhao China
Jin‐Sung Lee South Korea
Jingqi Zhang China
Peiling Li China
Guoyou Zhang China
Wei Han China
Ján Žižka relative to Vı́ctor Ruiz Mexico Vı́ctor Ruiz's profile →
Citations per field
00.5×10×15.5×
Vı́ctor Ruiz · 1×
Citations per year

Countries citing papers authored by Ján Žižka

Since Specialization
Citations

This map shows the geographic impact of Ján Žižka'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 Ján Žižka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ján Žižka more than expected).

Fields of papers citing papers by Ján Žižka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ján Žižka. 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 Ján Žižka. The network helps show where Ján Žižka may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ján Žižka, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ján Žižka Line = papers co-authored together Ján Žižka links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20231
2 20230
3 20219
4 201921
5 20150
6 201419
7
Parallel Processing of Very Many Textual Customers' Reviews Freely Written Down in Natural Languages
20123
8
Mining Significant Words from Customer Opinions Written in Different Natural Languages.
20112
9 201112
10 201117
11
Automatic Sentiment Analysis Using the Textual Pattern Content Similarity in Natural Language.
20101
12 201021
13 201026
14 200747
15 200714
16 200634
17 20047
18 200116
19 199811
20
Proceedings: EEG findings in children with Klinefelter's syndrome.
19752

About Ján Žižka

Ján Žižka is a scholar working on Emergency Medical Services, Pharmacy and Soil Science, having authored 113 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (10 papers), Chromosomal and Genetic Variations (8 papers), Text and Document Classification Technologies (8 papers), Advanced Text Analysis Techniques (7 papers), Soil Carbon and Nitrogen Dynamics (7 papers), Pediatric health and respiratory diseases (6 papers), Advanced MRI Techniques and Applications (6 papers) and Sentiment Analysis and Opinion Mining (5 papers). The work is most often cited by research in Hepatology (135 citations), Soil Science (135 citations) and Biomaterials (96 citations). Ján Žižka has collaborated with scholars based in Czechia, United States and Canada. Frequent co-authors include R. R. Simard, P Balícek, C. R. DE KIMPE, Pavel Ryška, L. Prokešová, T. Sen Tran, R. Lodinová‐Žádníková, Ramesh Raskar, I Šterzl and Antonı́n Krajina. Their work appears in journals such as SHILAP Revista de lepidopterología, Radiology and Journal of Hepatology.

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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