N. Cercone

2.1k citations
42 papers · 1.2k · h-index 15

Impact in

Papers in

    • Bayesian Modeling and Causal Inference 6
    • Natural Language Processing Techniques 5
    • Logic, Reasoning, and Knowledge 4
    • Algorithms and Data Compression 3
    • Data Mining Algorithms and Applications 18

N. Cercone

39 papers receiving 1.1k citations

Peers

N. Cercone
Comparison fields: 5 of 89
  • Signal Processing 423
  • Computational Theory and Mathematics 505
  • Information Systems 575
  • Artificial Intelligence 571
  • Computer Networks and Communications 280
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Nicolás Marı́n Spain
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Yun Sing Koh New Zealand
Yongjian Fu China
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Shyue-Liang Wang Taiwan
Yasuhiko Morimoto Japan
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Citations per field
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Citations per year

Countries citing papers authored by N. Cercone

Since Specialization
Citations

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

Fields of papers citing papers by N. Cercone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993244
2 2004194
3
Rough Sets and Data Mining: Analysis of Imprecise Data
1996157
4 1997155
5 200679
6 199948
7 199642
8 199732
9 199729
10 200229
11 200220
12 200619
13 198815
14 200515
15 200214
16 200613
17
Knowledge Engineering for a Process Design Domain.
199511
18 200611
19 20029
20 20046

About N. Cercone

N. Cercone is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Signal Processing and Computer Networks and Communications, having authored 42 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (18 papers), Rough Sets and Fuzzy Logic (16 papers), Data Management and Algorithms (12 papers), Bayesian Modeling and Causal Inference (6 papers), Natural Language Processing Techniques (5 papers), Advanced Database Systems and Queries (4 papers), Logic, Reasoning, and Knowledge (4 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Signal Processing (423 citations), Computational Theory and Mathematics (505 citations), Information Systems (575 citations), Artificial Intelligence (571 citations) and Computer Networks and Communications (280 citations). N. Cercone has collaborated with scholars based in Canada, Thailand and United States. Frequent co-authors include Tzu‐Yu Lin, Yin Cai, Ji Han, Vlado Kešelj, Tony Abou-Assaleh, Jiawei Han, Aijun An, Xiaohua Hu, Elissa Asp and Chee Seng Chan. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Mathematical and Computer Modelling, International Journal of Intelligent Systems, Applied Mathematics Letters and Computer.

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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