José Oncina
- Signal Processing top 2%
- Data Management and Algorithms 11
- Music and Audio Processing 4
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- Advanced Image and Video Retrieval Techniques 11
- Artificial Intelligence top 5%
- Algorithms and Data Compression 20
- Natural Language Processing Techniques 11
- Machine Learning and Algorithms 10
- Topic Modeling 4
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- semigroups and automata theory 5
José Oncina
31 papers receiving 646 citations
Peers
Comparison fields: 5 of 74
- Signal Processing 266
- Computer Vision and Pattern Recognition 276
- Artificial Intelligence 430
- Computational Theory and Mathematics 104
- Computer Graphics and Computer-Aided Design 21
Countries citing papers authored by José Oncina
This map shows the geographic impact of José Oncina'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 José Oncina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites José Oncina more than expected).
Fields of papers citing papers by José Oncina
This network shows the impact of papers produced by José Oncina. 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 José Oncina. The network helps show where José Oncina may publish in the future.
Co-authorship network
The 14 scholars most cited alongside José Oncina, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 2 | |
| 2 | 2016 | 10 | |
| 3 | 2016 | 5 | |
| 4 | Finding the Most Probable String and the Consensus String: an Algorithmic Study | 2011 | 1 |
| 5 | 2010 | 3 | |
| 6 | 2009 | 24 | |
| 7 | 2008 | 7 | |
| 8 | Spoken-Language Machine Translation in Limited Domains: Can it be Achieved by Finite-State Models? * | 2006 | 0 |
| 9 | 2004 | 1 | |
| 10 | Proceedings of the Workshop and Tutorial on Learning Context-Free Grammars | 2003 | 2 |
| 11 | 2003 | 0 | |
| 12 | 2003 | 8 | |
| 13 | 2001 | 7 | |
| 14 | 1999 | 62 | |
| 15 | 1998 | 16 | |
| 16 | 1998 | 7 | |
| 17 | Grammatical inference and applications : second International Colloquium, ICGI-94, Alicante, Spain, September 21-23, 1994 : proceedings | 1994 | 1 |
| 18 | Proceedings of the Second International Colloquium on Grammatical Inference and Applications | 1994 | 2 |
| 19 | 1993 | 104 | |
| 20 | Learning Locally Testable Languages in the Strict Sense. | 1990 | 36 |
About José Oncina
José Oncina is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 36 papers that have together received 708 indexed citations. Recurring topics across this work include Algorithms and Data Compression (20 papers), Advanced Image and Video Retrieval Techniques (11 papers), Natural Language Processing Techniques (11 papers), Data Management and Algorithms (11 papers), Machine Learning and Algorithms (10 papers), semigroups and automata theory (5 papers), Music and Audio Processing (4 papers) and Topic Modeling (4 papers). The work is most often cited by research in Signal Processing (266 citations), Computer Vision and Pattern Recognition (276 citations) and Artificial Intelligence (430 citations). José Oncina has collaborated with scholars based in Spain, France and Cuba. Frequent co-authors include Enrique Vidal, Luisa Micó, Rafael C. Carrasco, Jorge Calvo-Zaragoza, Pedro García, Marc Sebban, P. Castillo, Antonio Pertusa, Colin de la Higuera and Menno van Zaanen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Pattern Recognition.
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.