Ganesh Ramakrishnan
- Artificial Intelligence top 2%
- Topic Modeling 47
- Natural Language Processing Techniques 45
- Text and Document Classification Technologies 14
- Advanced Text Analysis Techniques 11
- Semantic Web and Ontologies 11
- Machine Learning and Algorithms 9
- Information Systems top 5%
- Web Data Mining and Analysis 11
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- Multimodal Machine Learning Applications 8
- Signal Processing top 10%
Ganesh Ramakrishnan
86 papers receiving 824 citations
Peers
Comparison fields: 5 of 91
- Artificial Intelligence 744
- Management Science and Operations Research 120
- Information Systems 212
- Computer Vision and Pattern Recognition 153
- Signal Processing 63
Countries citing papers authored by Ganesh Ramakrishnan
This map shows the geographic impact of Ganesh Ramakrishnan'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 Ganesh Ramakrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ganesh Ramakrishnan more than expected).
Fields of papers citing papers by Ganesh Ramakrishnan
This network shows the impact of papers produced by Ganesh Ramakrishnan. 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 Ganesh Ramakrishnan. The network helps show where Ganesh Ramakrishnan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ganesh Ramakrishnan, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 0 | |
| 4 | 2019 | 8 | |
| 5 | 2019 | 23 | |
| 6 | A framework for automatic question generation from text using deep reinforcement learning. | 2018 | 24 |
| 7 | 2015 | 2 | |
| 8 | 2015 | 12 | |
| 9 | Labeling Documents in Search Collection: Evolving Classifiers on a Semantically Relevant Label Space. | 2014 | 0 |
| 10 | Enriching concept search across semantic web ontologies | 2013 | 1 |
| 11 | SATTY : Word Sense Induction Application in Web Search Clustering | 2013 | 3 |
| 12 | Learning to Generate Diversified Query Interpretations using Biconvex Optimization | 2013 | 1 |
| 13 | Error tracking in search engine development | 2012 | 1 |
| 14 | Towards Efficient Named-Entity Rule Induction for Customizability | 2012 | 8 |
| 15 | 2011 | 7 | |
| 16 | Efficient Rule Ensemble Learning using Hierarchical Kernels | 2011 | 8 |
| 17 | Learning Decision Lists with Known Rules for Text Mining | 2008 | 3 |
| 18 | A Gloss-centered Algorithm for Disambiguation | 2004 | 5 |
| 19 | Passage Scoring for Question Answering via Bayesian Inference on Lexical Relations. | 2003 | 5 |
| 20 | Text Representation with WordNet Synsets using Soft Sense Disambiguation. | 2003 | 5 |
About Ganesh Ramakrishnan
Ganesh Ramakrishnan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 104 papers that have together received 914 indexed citations. Recurring topics across this work include Topic Modeling (47 papers), Natural Language Processing Techniques (45 papers), Text and Document Classification Technologies (14 papers), Advanced Text Analysis Techniques (11 papers), Web Data Mining and Analysis (11 papers), Semantic Web and Ontologies (11 papers), Machine Learning and Algorithms (9 papers) and Multimodal Machine Learning Applications (8 papers). The work is most often cited by research in Artificial Intelligence (744 citations), Management Science and Operations Research (120 citations) and Information Systems (212 citations). Ganesh Ramakrishnan has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Soumen Chakrabarti, Amit Singh, Pushpak Bhattacharyya, Rishabh Iyer, Yuan-Fang Li, Vishwajeet Kumar, Sachindra Joshi, Ashutosh Joshi, Somnath Banerjee and Sunita Sarawagi. Their work appears in journals such as Neurocomputing, Machine Learning and Journal of Machine Learning Research.
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.