Eric Mays

904 citations
28 papers · 656 · h-index 13

Impact in

    • Natural Language Processing Techniques
    • Semantic Web and Ontologies
    • Topic Modeling
    • Logic, Reasoning, and Knowledge
    • Algorithms and Data Compression
    • Data Management and Algorithms

Papers in

Eric Mays

27 papers receiving 558 citations

Peers

Eric Mays
Comparison fields: 5 of 53
  • Artificial Intelligence 520
  • Signal Processing 100
  • Computer Networks and Communications 168
  • Issues, ethics and legal aspects 5
  • Information Systems 94
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Citations per year

Countries citing papers authored by Eric Mays

Since Specialization
Citations

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

Fields of papers citing papers by Eric Mays

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Eric Mays, 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 Eric Mays Line = papers co-authored together Eric Mays links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1991199
2 199169
3
Role grouping as an extension to the description logic of Ontylog, motivated by concept modeling in SNOMED.
200249
4
Scalable and expressive medical terminologies.
199644
5 199142
6 198736
7 198326
8
Failures in natural language systems: applications to data base query systems
198025
9 198922
10 199119
11 199315
12 199114
13
A non-well-founded approach to terminological cycles
199213
14
Taking the Initiative in Natural Language Data Base Interactions: Monitoring as Response.
198211
15
Natural language interaction with dynamic knowledge bases: monitoring as response
198111
16
Standards-Based Sharable Active Guideline Environment (SAGE): A Project to Develop a Universal Framework for Encoding and Disseminating Electronic Clinical Practice Guidelines
200210
17
Monitors as responses to questions: determining competence
19829
18 19839
19 19838
20 20037

About Eric Mays

Eric Mays is a scholar working on Artificial Intelligence, Computer Networks and Communications, Molecular Biology, Information Systems and Computational Theory and Mathematics, having authored 28 papers that have together received 656 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (22 papers), Logic, Reasoning, and Knowledge (14 papers), Advanced Database Systems and Queries (8 papers), Natural Language Processing Techniques (7 papers), AI-based Problem Solving and Planning (3 papers), Multi-Agent Systems and Negotiation (3 papers), Biomedical Text Mining and Ontologies (3 papers) and Service-Oriented Architecture and Web Services (2 papers). The work is most often cited by research in Artificial Intelligence (520 citations), Signal Processing (100 citations), Computer Networks and Communications (168 citations), Issues, ethics and legal aspects (5 citations) and Information Systems (94 citations). Eric Mays has collaborated with scholars based in United States. Frequent co-authors include Fred J. Damerau, Robert L. Mercer, Sitaram Lanka, Bonnie Webber, Frank J. Oles, Kent A. Spackman, Aravind K. Joshi, James H. Griesmer, Chidanand Apté and Brian E. White. Their work appears in journals such as Information Processing & Management, IBM Journal of Research and Development, IEEE Transactions on Knowledge and Data Engineering, ACM SIGMOD Record and Computers & Mathematics with Applications.

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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