Nick Cercone

4.1k citations
128 papers · 2.0k · h-index 22

Impact in

Papers in

    • Natural Language Processing Techniques 28
    • Topic Modeling 19
    • Semantic Web and Ontologies 14
    • Logic, Reasoning, and Knowledge 8
    • Data Mining Algorithms and Applications 29

Nick Cercone

122 papers receiving 1.8k citations

Peers

Nick Cercone
Comparison fields: 5 of 122
  • Computational Theory and Mathematics 675
  • Information Systems 944
  • Signal Processing 409
  • Artificial Intelligence 1.2k
  • Computer Networks and Communications 257
Replace Wee Keong Ng with:
Wee Keong Ng Singapore
Craig Silverstein United States
Howard J. Hamilton Canada
Ivo Düntsch United Kingdom
Yongjian Fu China
Raffaele Perego Italy
Salvatore Orlando Italy
Erich Neuhold Germany
Wensheng Gan China
José María Luna Spain
Nick Cercone relative to Wee Keong Ng Singapore Wee Keong Ng's profile →
Citations per field
00.5×4.3×
Wee Keong Ng · 1×
Citations per year

Countries citing papers authored by Nick Cercone

Since Specialization
Citations

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

Fields of papers citing papers by Nick Cercone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1
N-GRAM-BASED AUTHOR PROFILES FOR AUTHORSHIP ATTRIBUTION
2003262
2 1995241
3
Knowledge Discovery in Databases: An Attribute-Oriented Approach
1992231
4 199696
5
Detection of New Malicious Code Using N-grams Signatures.
200467
6
The knowledge frontier: essays in the representation of knowledge
198755
7 200349
8 200748
9 200148
10 200939
11 200037
12
Using rough sets as tools for knowledge discovery
199536
13 201234
14 201331
15 198729
16 200828
17 199926
18 199924
19 201224
20 200923

About Nick Cercone

Nick Cercone is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Signal Processing and Computer Networks and Communications, having authored 128 papers that have together received 2.0k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (29 papers), Natural Language Processing Techniques (28 papers), Rough Sets and Fuzzy Logic (26 papers), Data Management and Algorithms (23 papers), Topic Modeling (19 papers), Semantic Web and Ontologies (14 papers), Advanced Database Systems and Queries (9 papers) and Logic, Reasoning, and Knowledge (8 papers). The work is most often cited by research in Computational Theory and Mathematics (675 citations), Information Systems (944 citations), Signal Processing (409 citations), Artificial Intelligence (1.2k citations) and Computer Networks and Communications (257 citations). Nick Cercone has collaborated with scholars based in Canada, Thailand and United States. Frequent co-authors include Xiaohua Hu, Yandong Cai, Fuchun Peng, Jiawei Han, Calvin Thomas, Gordon McCalla, Aijun An, Ning Shan, Wojciech Ziarko and Howard J. Hamilton. Their work appears in journals such as Computers & Mathematics with Applications, Knowledge and Information Systems, Computers & Education, Engineering Applications of Artificial Intelligence and Applied Mathematics Letters.

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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