Anna Wilbik

1.6k citations
79 papers · 798 · h-index 17

Impact in

    • Data Management and Algorithms
    • Time Series Analysis and Forecasting
    • Semantic Web and Ontologies
    • Advanced Text Analysis Techniques
    • Natural Language Processing Techniques

Papers in

    • Semantic Web and Ontologies 14
    • Privacy-Preserving Technologies in Data 10
    • Natural Language Processing Techniques 8
    • Data Management and Algorithms 27
    • Time Series Analysis and Forecasting 11

Anna Wilbik

74 papers receiving 770 citations

Peers

Anna Wilbik
Comparison fields: 5 of 95
  • Signal Processing 305
  • Artificial Intelligence 491
  • Health Informatics 13
  • Computational Theory and Mathematics 160
  • Management Science and Operations Research 111
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Citations per field
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Citations per year

Countries citing papers authored by Anna Wilbik

Since Specialization
Citations

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

Fields of papers citing papers by Anna Wilbik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008116
2 201136
3 201434
4 202033
5 202227
6
Using fuzzy linguistic summaries for the comparison of time series: an application to the analysis of investment fund quotations
200925
7 201025
8 201225
9 201724
10 201222
11 200622
12 200921
13 200720
14 202019
15 201918
16 202117
17 200617
18 200814
19 202113
20 202112

About Anna Wilbik

Anna Wilbik is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Management Information Systems and Computational Theory and Mathematics, having authored 79 papers that have together received 798 indexed citations. Recurring topics across this work include Data Management and Algorithms (27 papers), Semantic Web and Ontologies (14 papers), Data Mining Algorithms and Applications (12 papers), Rough Sets and Fuzzy Logic (11 papers), Time Series Analysis and Forecasting (11 papers), Privacy-Preserving Technologies in Data (10 papers), Business Process Modeling and Analysis (9 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Signal Processing (305 citations), Artificial Intelligence (491 citations), Health Informatics (13 citations), Computational Theory and Mathematics (160 citations) and Management Science and Operations Research (111 citations). Anna Wilbik has collaborated with scholars based in Netherlands, Poland and United States. Frequent co-authors include Janusz Kacprzyk, Sławomir Zadrożny, James M. Keller, Remco Dijkman, Gregory L. Alexander, Paul Grefen, James C. Bezdek, Marijn ten Thij, Uzay Kaymak and Marek Reformat. Their work appears in journals such as Software & Systems Modeling, Fuzzy Sets and Systems, International Journal of Intelligent Systems, IEEE Transactions on Fuzzy Systems and Semantic Web.

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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