Miguel Ballesteros
About
In The Last Decade
Miguel Ballesteros
54 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Artificial Intelligence 3.4k
- Computer Vision and Pattern Recognition 455
- Molecular Biology 452
- Information Systems 399
- Management Science and Operations Research 289
Countries citing papers authored by Miguel Ballesteros
This map shows the geographic impact of Miguel Ballesteros'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 Miguel Ballesteros with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel Ballesteros more than expected).
Fields of papers citing papers by Miguel Ballesteros
This network shows the impact of papers produced by Miguel Ballesteros. 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 Miguel Ballesteros. The network helps show where Miguel Ballesteros may publish in the future.
Co-authorship network of co-authors of Miguel Ballesteros
This figure shows the co-authorship network connecting the top 25 collaborators of Miguel Ballesteros. A scholar is included among the top collaborators of Miguel Ballesteros 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 Miguel Ballesteros. Miguel Ballesteros is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 4 | |
| 3 | 19 | |
| 4 | Multilingual Neural Machine Translation with Task-Specific Attention | 23 |
| 5 | 97 | |
| 6 | 89 | |
| 7 | One Parser, Many Languages. | 7 |
| 8 | Transition-Based Dependency Parsing with Stack Long Short-Term Memory breakdown → | 355 |
| 9 | ViZPar: A GUI for ZPar with Manual Feature Selection | 2 |
| 10 | Automatic Feature Selection for Agenda-Based Dependency Parsing | 8 |
| 11 | Deep-Syntactic Parsing | 10 |
| 12 | Exploring Automatic Feature Selection for Transition-Based Dependency Parsing | 2 |
| 13 | Finding Dependency Parsing Limits over a Large Spanish Corpus | 7 |
| 14 | Extracting Drug-Drug Interaction from Text Using Negation Features | 4 |
| 15 | Analyzing the CoNLL--X Shared Task from a Sentence Accuracy Perspective | 1 |
| 16 | Are the existing training corpora unnecessarily large | 1 |
| 17 | UCM-2: a Rule-Based Approach to Infer the Scope of Negation via Dependency Parsing | 5 |
| 18 | MaltOptimizer: A System for MaltParser Optimization | 40 |
| 19 | UCM-I: A Rule-based Syntactic Approach for Resolving the Scope of Negation | 12 |
| 20 | Inferring the Scope of Negation and Speculation Via Dependency Analysis. | 0 |
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.