Guy Feigenblat

569 citations
25 papers · 350 · h-index 11

Impact in

Papers in

    • Topic Modeling 9
    • Natural Language Processing Techniques 6
    • Machine Learning and Algorithms 5
    • Sentiment Analysis and Opinion Mining 4
    • Advanced Text Analysis Techniques 3
    • Algorithms and Data Compression 3

Guy Feigenblat

25 papers receiving 313 citations

Peers

Guy Feigenblat
Comparison fields: 5 of 81
  • Artificial Intelligence 185
  • Signal Processing 26
  • Information Systems 53
  • Marketing 21
  • Plant Science 80
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Aakanksha Sharaff India
Shaohong Fu China
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Citations per year

Countries citing papers authored by Guy Feigenblat

Since Specialization
Citations

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

Fields of papers citing papers by Guy Feigenblat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Guy Feigenblat, 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 Guy Feigenblat Line = papers co-authored together Guy Feigenblat links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200292
2 201444
3 201734
4 201626
5 202023
6 201620
7 202014
8 202113
9 202112
10 202011
11 201911
12 20209
13 20208
14 20118
15 20116
16 20113
17 20102
18 20202
19 20152
20 20162

About Guy Feigenblat

Guy Feigenblat is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 25 papers that have together received 350 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (6 papers), Machine Learning and Algorithms (5 papers), Sentiment Analysis and Opinion Mining (4 papers), Caching and Content Delivery (3 papers), Advanced Text Analysis Techniques (3 papers), Data Quality and Management (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Artificial Intelligence (185 citations), Signal Processing (26 citations), Information Systems (53 citations), Marketing (21 citations) and Plant Science (80 citations). Guy Feigenblat has collaborated with scholars based in Israel, United States and India. Frequent co-authors include Haggai Roitman, David Konopnicki, Aharon Rabinkov, Irina Shin, David Mirelman, Talia Miron, Meir Wilchek, Lev Weiner, Michal Shmueli-Scheuer and Ely Porat. Their work appears in journals such as Theoretical Computer Science, Algorithmica, IBM Journal of Research and Development, Information and Computation and Journal of Computer and System Sciences.

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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