John M. Zelle
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Computer Science Applications top 10%
- Computer Networks and Communications
- Topics
- Natural Language Processing Techniques (7 papers)Topic Modeling (5 papers)Logic, Reasoning, and Knowledge (4 papers)
- Cited by
- Artificial IntelligenceComputer Science ApplicationsComputer Vision and Pattern Recognition
- Journals
- AI MagazineInternational Joint Conference on Artificial IntelligenceNational Conference on Artificial Intelligence
- Partner nations
- United States
In The Last Decade
John M. Zelle
16 papers receiving 558 citations
Peers
Comparison fields: 5 of 65
- Artificial Intelligence 528
- Computer Vision and Pattern Recognition 112
- Information Systems 106
- Computer Science Applications 46
- Computer Networks and Communications 33
Countries citing papers authored by John M. Zelle
This map shows the geographic impact of John M. Zelle'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 M. Zelle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John M. Zelle more than expected).
Fields of papers citing papers by John M. Zelle
This network shows the impact of papers produced by John M. Zelle. 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 M. Zelle. The network helps show where John M. Zelle may publish in the future.
Co-authorship network of co-authors of John M. Zelle
This figure shows the co-authorship network connecting the top 25 collaborators of John M. Zelle. A scholar is included among the top collaborators of John M. Zelle based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John M. Zelle. John M. Zelle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Python Programming: An Introduction to Computer Science 2nd Edition | 3 |
| 2 | Data Structures and Algorithms Using Python and C | 1 |
| 3 | 4 | |
| 4 | 11 | |
| 5 | 7 | |
| 6 | 16 | |
| 7 | 10 | |
| 8 | Python Programming: An Introduction to Computer Science | 69 |
| 9 | 27 | |
| 10 | Corpus-Based Approaches to Semantic Interpretation in Natural Language Processing | 27 |
| 11 | Learning to parse database queries using inductive logic programming | 364 |
| 12 | Using inductive logic programming to automate the construction of natural language parsers | 17 |
| 13 | Inducing deterministic prolog parsers from treebanks: a machine learning approach | 16 |
| 14 | 4 | |
| 15 | Learning semantic grammars with constructive inductive logic programming | 51 |
| 16 | Combining FOIL and EBG To Speed-up Logic Programs | 24 |
| 17 | Learning Search-Control Heuristics For Logic Programs: Applications ToSpeed-up Learning and LanguageAcquisitions | 1 |
About John M. Zelle
John M. Zelle is a scholar working on Artificial Intelligence, Human-Computer Interaction and Media Technology, having authored 17 papers that have together received 652 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Topic Modeling (5 papers) and Logic, Reasoning, and Knowledge (4 papers). The work is most often cited by research in Artificial Intelligence (528 citations), Computer Science Applications (46 citations) and Computer Vision and Pattern Recognition (112 citations). John M. Zelle has collaborated with scholars based in United States. Frequent co-authors include Raymond J. Mooney, Hwee Tou Ng, C. Figura, Brad Miller and Mark Guzdial. Their work appears in journals such as AI Magazine, International Joint Conference on Artificial Intelligence 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.