Daniel Gildea
About
In The Last Decade
Daniel Gildea
115 papers receiving 4.9k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 5.1k
- Molecular Biology 452
- Computer Vision and Pattern Recognition 409
- Language and Linguistics 371
- Information Systems 364
Countries citing papers authored by Daniel Gildea
This map shows the geographic impact of Daniel Gildea'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 Daniel Gildea with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gildea more than expected).
Fields of papers citing papers by Daniel Gildea
This network shows the impact of papers produced by Daniel Gildea. 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 Daniel Gildea. The network helps show where Daniel Gildea may publish in the future.
Co-authorship network of co-authors of Daniel Gildea
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Gildea. A scholar is included among the top collaborators of Daniel Gildea 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 Daniel Gildea. Daniel Gildea is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Efficient Outside Computation | 0 |
| 2 | 112 | |
| 3 | Semantic Roles for String to Tree Machine Translation | 14 |
| 4 | Improving the IBM Alignment Models Using Variational Bayes | 14 |
| 5 | Tuning as Linear Regression | 8 |
| 6 | Optimal Head-Driven Parsing Complexity for Linear Context-Free Rewriting Systems | 4 |
| 7 | Issues Concerning Decoding with Synchronous Context-free Grammar | 10 |
| 8 | Terminal-Aware Synchronous Binarization | 3 |
| 9 | Optimal Parsing Strategies for Linear Context-Free Rewriting Systems | 18 |
| 10 | Semantic Role Features for Machine Translation | 61 |
| 11 | Factors Affecting the Accuracy of Korean Parsing | 15 |
| 12 | Parsers as language models for statistical machine translation | 18 |
| 13 | Bayesian Learning of Non-Compositional Phrases with Synchronous Parsing | 49 |
| 14 | Worst-Case Synchronous Grammar Rules | 8 |
| 15 | Optimizing Grammars for Minimum Dependency Length | 27 |
| 16 | Enumeration of Factorizable Multi-Dimensional Permutations | 2 |
| 17 | Syntactic Features for Evaluation of Machine Translation | 113 |
| 18 | Dependencies vs. Constituents for Tree-Based Alignment | 14 |
| 19 | Identifying semantic relations in text | 0 |
| 20 | Corpus Variation and Parser Performance | 189 |
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.