Rajeev Sangal
About
In The Last Decade
Rajeev Sangal
36 papers receiving 599 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 626
- Computer Vision and Pattern Recognition 109
- Information Systems 64
- Language and Linguistics 58
- Molecular Biology 32
Countries citing papers authored by Rajeev Sangal
This map shows the geographic impact of Rajeev Sangal'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 Rajeev Sangal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajeev Sangal more than expected).
Fields of papers citing papers by Rajeev Sangal
This network shows the impact of papers produced by Rajeev Sangal. 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 Rajeev Sangal. The network helps show where Rajeev Sangal may publish in the future.
Co-authorship network of co-authors of Rajeev Sangal
This figure shows the co-authorship network connecting the top 25 collaborators of Rajeev Sangal. A scholar is included among the top collaborators of Rajeev Sangal 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 Rajeev Sangal. Rajeev Sangal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Novel Approach Towards Incorporating Context Processing Capabilities in NLIDB System | 5 |
| 2 | Stance Classification in Online Debates by Recognizing Users' Intentions | 11 |
| 3 | Intra-Chunk Dependency Annotation : Expanding Hindi Inter-Chunk Annotated Treebank | 6 |
| 4 | Clausal parsing helps data-driven dependency parsing: Experiments with Hindi | 5 |
| 5 | Coupling Statistical Machine Translation with Rule-based Transfer and Generation. | 12 |
| 6 | Two Methods to Incorporate 'Local Morphosyntactic' Features in Hindi Dependency Parsing | 18 |
| 7 | Improving Data Driven Dependency Parsing using Clausal Information | 13 |
| 8 | 3 | |
| 9 | On the Role of Morphosyntactic Features in Hindi Dependency Parsing | 20 |
| 10 | A Discriminative Approach for Dependency Based Statistical Machine Translation | 2 |
| 11 | Constraint Based Hybrid Approach to Parsing Indian Languages | 9 |
| 12 | All Words Unsupervised Semantic Category Labeling for Hindi | 2 |
| 13 | 2 | |
| 14 | 11 | |
| 15 | Dependency Annotation Scheme for Indian Languages | 90 |
| 16 | Two approaches for building an unsupervised dependency parser and their other applications | 1 |
| 17 | Unit selection voice for Amharic using Festvox. | 11 |
| 18 | Unsupervised Improvement of Morphological Analyzer for Inflectionally Rich Languages. | 10 |
| 19 | Programming paradigms in LISP | 5 |
| 20 | Programming Paradigms in LISP: Tools, Techniques, and Principles | 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.