John Cabral

541 citations
8 papers · 415 · h-index 6

Impact in

    • Semantic Web and Ontologies
    • Natural Language Processing Techniques
    • Topic Modeling
    • Advanced Text Analysis Techniques
    • Logic, Reasoning, and Knowledge
    • AI-based Problem Solving and Planning
    • Service-Oriented Architecture and Web Services

Papers in

Journals
Lecture notes in computer science (1 paper)The Florida AI Research Society (1 paper)Maryland Shared Open Access Repository (USMAI Consortium) (4 papers)National Conference on Artificial Intelligence (1 paper)
Partner nations
BrazilAustralia

In The Last Decade

John Cabral

8 papers receiving 354 citations

Peers

John Cabral
Comparison fields: 5 of 45
  • Artificial Intelligence 367
  • Information Systems 111
  • Management Science and Operations Research 38
  • Computer Networks and Communications 46
  • Signal Processing 21
Replace Jussi Kurki with:
Jussi Kurki Finland
Paraskevi Raftopoulou Greece
Christine Golbreich France
Jordi Turmo Spain
Elmar Haußmann Germany
Xing Jiang Singapore
Brigitte Mathiak Germany
Anna Tordai Netherlands
Ralph R. Swick United States
Danica Damljanović United Kingdom
John Cabral relative to Jussi Kurki Finland Jussi Kurki's profile →
Citations per field
00.5×1.5×2.1×
Jussi Kurki · 1×
Citations per year

Countries citing papers authored by John Cabral

Since Specialization
Citations

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

Fields of papers citing papers by John Cabral

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside John Cabral, 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 John Cabral Line = papers co-authored together John Cabral links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2006256
2 200587
3 200628
4 200626
5 20058
6
Methods of Rule Acquisition in the TextLearner System.
20095
7 20054
8 20061

About John Cabral

John Cabral is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Hardware and Architecture and Computational Theory and Mathematics, having authored 8 papers that have together received 415 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Semantic Web and Ontologies (5 papers), Topic Modeling (4 papers), Parallel Computing and Optimization Techniques (1 paper), Speech and dialogue systems (1 paper), Formal Methods in Verification (1 paper), Distributed and Parallel Computing Systems (1 paper) and Distributed systems and fault tolerance (1 paper). The work is most often cited by research in Artificial Intelligence (367 citations), Information Systems (111 citations), Management Science and Operations Research (38 citations), Computer Networks and Communications (46 citations) and Signal Processing (21 citations). John Cabral has collaborated with scholars based in Brazil and Australia. Frequent co-authors include Michael Witbrock, Cynthia Matuszek, David Baxter, Jon Curtis, Doug Lenat, David Schneider, Peter J. Wagner, Douglas B. Lenat, Jorge Figueiredo and Dalton Guerrero. Their work appears in journals such as Lecture notes in computer science, The Florida AI Research Society, Maryland Shared Open Access Repository (USMAI Consortium) and National Conference on Artificial Intelligence.

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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