Ergun Biçici
About
In The Last Decade
Ergun Biçici
42 papers receiving 278 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 327
- Molecular Biology 45
- Computer Vision and Pattern Recognition 40
- Information Systems 14
- Language and Linguistics 11
Countries citing papers authored by Ergun Biçici
This map shows the geographic impact of Ergun Biçici'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 Ergun Biçici with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ergun Biçici more than expected).
Fields of papers citing papers by Ergun Biçici
This network shows the impact of papers produced by Ergun Biçici. 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 Ergun Biçici. The network helps show where Ergun Biçici may publish in the future.
Co-authorship network of co-authors of Ergun Biçici
This figure shows the co-authorship network connecting the top 25 collaborators of Ergun Biçici. A scholar is included among the top collaborators of Ergun Biçici 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 Ergun Biçici. Ergun Biçici is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 4 | |
| 8 | 9 | |
| 9 | CNGL-CORE: Referential Translation Machines for Measuring Semantic Similarity | 8 |
| 10 | CNGL: Grading Student Answers by Acts of Translation | 6 |
| 11 | Referential Translation Machines for Quality Estimation | 23 |
| 12 | Feature Decay Algorithms for Fast Deployment of Accurate Statistical Machine Translation Systems | 14 |
| 13 | 18 | |
| 14 | 18 | |
| 15 | RegMT System for Machine Translation, System Combination, and Evaluation | 10 |
| 16 | Instance Selection for Machine Translation using Feature Decay Algorithms | 44 |
| 17 | L1 Regularized Regression for Reranking and System Combination in Machine Translation | 5 |
| 18 | Adaptive Model Weighting and Transductive Regression for Predicting Best System Combinations | 3 |
| 19 | Clustering Word Pairs to Answer Analogy Questions | 2 |
| 20 | 1 |
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.